Recession Indicators

Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}

## [1] "CPIAUCSL"

## [1] "CPIAUCSL"
## [1] "USREC"
## [1] "UNRATE"
## [1] "PCEPI"
## [1] "CCSA"
## [1] "CCNSA"
## [1] "NPPTTL"
## [1] "U6RATE"
## [1] "PAYNSA"
## [1] "TABSHNO"
## [1] "HNONWPDPI"
## [1] "INDPRO"
## [1] "RRSFS"
## [1] "RSALES"
## [1] "W875RX1"
## [1] "RPI"
## [1] "PCOPPUSDM"
## [1] "NOBL"
## [1] "SCHD"
## [1] "PFF"
## [1] "HPI"
## [1] "GSFTX"
## [1] "LFMIX"
## [1] "LFMCX"
## [1] "LFMAX"
## [1] "LCSIX"
## [1] "BSV"
## [1] "VBIRX"
## [1] "BIV"
## [1] "VFSUX"
## [1] "LTUIX"
## [1] "PTTPX"
## [1] "NERYX"
## [1] "STIGX"
## [1] "HLGAX"
## [1] "FTRGX"
## [1] "THIIX"
## [1] "PTTRX"
## [1] "BFIGX"
## [1] "VTWO"
## [1] "EIFAX"
## [1] "ASDAX"

## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "TRBUX"
## [1] "PRVIX"
## [1] "PRWCX"
## [1] "ADOZX"
## [1] "MERFX"
## [1] "CMNIX"
## [1] "CIHEX"
## [1] "IMPCH"
## [1] "EXPCH"
## [1] "IMPMX"
## [1] "EXPMX"
## [1] "HSN1FNSA"
## [1] "HNFSUSNSA"
## [1] "BUSLOANS"
## [1] "TOTCI"
## [1] "BUSLOANSNSA"
## [1] "REALLNNSA"
## [1] "REALLN"
## [1] "RELACBW027NBOG"
## [1] "RELACBW027SBOG"
## [1] "RREACBM027NBOG"
## [1] "RREACBM027SBOG"
## [1] "RREACBW027SBOG"
## [1] "RREACBW027NBOG"
## [1] "MORTGAGE30US"
## [1] "CONSUMERNSA"
## [1] "TOTLLNSA"
## [1] "DPSACBW027SBOG"
## [1] "DRCLACBS"
## [1] "TOTCINSA"
## [1] "SRPSABSNNCB"
## [1] "ASTLL"
## [1] "FBDILNECA"
## [1] "ASOLAL"
## [1] "ASTMA"
## [1] "ASHMA"
## [1] "ASMRMA"
## [1] "ASCMA"
## [1] "ASFMA"
## [1] "CCLBSHNO"
## [1] "FBDSILQ027S"
## [1] "FBLL"
## [1] "NCBDBIQ027S"
## [1] "DGS10"
## [1] "^TNX"

## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "DGS30"
## [1] "DGS1"
## [1] "DGS2"
## [1] "TB3MS"
## [1] "DTB3"
## [1] "^IRX"

## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "DCOILWTICO"
## [1] "DCOILBRENTEU"
## [1] "NEWORDER"
## [1] "ALTSALES"
## [1] "ICSA"
## [1] "^GSPC"
## [1] "FXAIX"
## [1] "FTIHX"
## [1] "MDIZX"
## [1] "DODIX"
## [1] "^RLG"

## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "^DJI"
## [1] "^STOXX50E"

## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.

## [1] "EFA"
## [1] "GDP"
## [1] "FNDEFX"
## [1] "FDEFX"
## [1] "GDPNOW"
## [1] "GDPC1"
## [1] "GDPDEF"
## [1] "VIG"
## [1] "WLRRAL"
## [1] "FEDFUNDS"
## [1] "GPDI"
## [1] "W790RC1Q027SBEA"
## [1] "MZMV"
## [1] "M1"
## [1] "M2"
## [1] "OPHNFB"
## [1] "IPMAN"
## [1] "IWD"
## [1] "GS5"
## [1] "PSAVERT"
## [1] "VIXCLS"
## [1] "VXX"
## [1] "HOUST1F"
## [1] "GFDEBTN"
## [1] "HOUST"
## [1] "EXHOSLUSM495S"
## [1] "MSPUS"
## [1] "UMDMNO"
## [1] "DGORDER"
## [1] "CSUSHPINSA"
## [1] "GFDEGDQ188S"
## [1] "FYFSD"
## [1] "FYFSGDA188S"
## [1] "GDX"
## [1] "XLE"
## [1] "GSG"
## [1] "WALCL"
## [1] "OUTMS"
## [1] "MANEMP"
## [1] "PRS30006163"
## [1] "BAMLC0A3CA"
## [1] "AAA"
## [1] "SOFR"
## [1] "SOFRVOL"
## [1] "SOFR99"
## [1] "SOFR75"
## [1] "SOFR25"
## [1] "SOFR1"
## [1] "OBFR"
## [1] "OBFR99"
## [1] "OBFR75"
## [1] "OBFR25"
## [1] "OBFR1"
## [1] "RPONTSYD"
## [1] "IOER"
## [1] "WRESBAL"
## [1] "EXCSRESNW"
## [1] "ECBASSETS"
## [1] "EUNNGDP"
## [1] "CEU0600000007"
## [1] "CURRENCY"
## [1] "WCURRNS"
## [1] "BOGMBASE"
## [1] "PRS88003193"
## [1] "PPIACO"
## [1] "PCUOMFGOMFG"
## [1] "POPTHM"
## [1] "POPTHM"
## [1] "CLF16OV"
## [1] "LNU01000000"
## [1] "LNU03000000"
## [1] "UNEMPLOY"
## [1] "RSAFS"
## [1] "FRGSHPUSM649NCIS"
## [1] "BOPGTB"
## [1] "TERMCBPER24NS"
## [1] "A065RC1A027NBEA"
## [1] "PI"
## [1] "PCE"
## [1] "A053RC1Q027SBEA"
## [1] "CPROFIT"
## [1] "SPY"
## [1] "MDY"
## [1] "EES"
## [1] "IJR"
## [1] "VGSTX"
## [1] "VFINX"
## [1] "VOE"
## [1] "VOT"
## [1] "TMFGX"

## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## [1] "IWM"
## [1] "ONEQ"
## [1] "FSMAX"
## [1] "FXNAX"
## [1] "HAINX"
## [1] "HNACX"
## [1] "VEU"
## [1] "VEIRX"
## [1] "BIL"
## [1] "IVOO"
## [1] "VO"
## [1] "CZA"
## [1] "VYM"
## [1] "ACWI"
## [1] "SLY"
## [1] "QQQ"
## [1] "HYMB"
## [1] "GOLD"
## [1] "BKR"
## [1] "SLB"
## [1] "HAL"
## [1] "IP"
## [1] "PKG"
## [1] "UPS"
## [1] "FDX"
## [1] "T"
## [1] "VZ"

Load up the EIA data

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date

## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...

## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 736680 Columns: 15
## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date
## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
## Downloading GitHub repo RamiKrispin/coronavirus@master

##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpOuWRlN\remotes817859a87e60\RamiKrispin-coronavirus-89f129d/DESCRIPTION'
## 
  
  
  
-  preparing 'coronavirus': (1.6s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts (391ms)
## 
  
  
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 

## Caught an warning!

## <simpleWarning: package 'coronavirus' is in use and will not be installed>

## `summarise()` has grouped output by 'country'. You can override using the
## `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.symbols)

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)

## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRVIX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "FXAIX.Volume has zero or negative values. Log series will be zero."
## [1] "FTIHX.Volume has zero or negative values. Log series will be zero."
## [1] "MDIZX.Volume has zero or negative values. Log series will be zero."
## [1] "DODIX.Volume has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "FSMAX.Volume has zero or negative values. Log series will be zero."
## [1] "FXNAX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "HNACX.Volume has zero or negative values. Log series will be zero."
## [1] "VEIRX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."

df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

• Go long on short term bonds, rather than just roll out of the market. That way at least some returns would be generated during recessions.
• Refine the recession indicator.

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 20.73 compares to a historical mean value over the last decade of 18.62. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

• S&P 500 Volume, last updated on 2022-06-16, is flat over the last year and flat over the last month.

Unemployment

• Headline unemployment (U-3) stands at 3.60% (last updated on 2022-05-01) which is near the 1-year average of 4.19% and rising with respect to the low in the last twelve months of 3.60%. Unlikely the rate will drop again.

• Payrolls (BLS data, NSA) year-over-year stands at 3.62% which is above the 1-year average of 4.45% and falling with respect to the peak, in the last twelve months, of 5.51%.

• Jobless claims (ICSA data) year-over-year stands at -46.26% (last updated on 2022-06-11) which is in-line with the 1-year average of -65.32% and below the peak, in the last twelve months, of -44.86%.

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

• Real personal income year over year growth stands at 1.22% (last updated on 2022-04-01). This is below the recent peak of 5.13%.

Yield Curve and Bond Market

• The 10-year to 3-month yield stands at 1.64% (last updated on 2022-06-15). This is above the recent low of 1.14%. The trend is positive over the last year and flat over the last month.

• Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  

6-Month High

	string.symbol	string.description
1	CPIAUCSL	Consumer Price Index for All Urban Consumers: All Items
4	PCEPI	Personal Consumption Expenditures: Chain-type Price Index
7	NPPTTL	Total Nonfarm Private Payroll Employment (ADP)
9	PAYNSA	All Employees: Total Nonfarm Payrolls (NSA)
12	INDPRO	Industrial Production Index
14	RSALES	Real Retail Sales (DISCONTINUED)
15	W875RX1	Real personal income excluding current transfer receipts
17	PCOPPUSDM	Global price of Copper
55	HNFSUSNSA	New One Family Houses for Sale in the United States (Monthly, NSA)
56	BUSLOANS	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
57	TOTCI	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
58	BUSLOANSNSA	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
59	REALLNNSA	Real Estate Loans, All Commercial Banks (Monthly, NSA)
60	REALLN	Real Estate Loans, All Commercial Banks (Monthly, SA)
61	RELACBW027NBOG	Real Estate Loans, All Commercial Banks (Weekly, NSA)
62	RELACBW027SBOG	Real Estate Loans, All Commercial Banks (Weekly, SA)
63	RREACBM027NBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
64	RREACBM027SBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
65	RREACBW027SBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
66	RREACBW027NBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
67	MORTGAGE30US	30-Year Fixed Rate Mortgage Average in the United States
68	CONSUMERNSA	Consumer Loans, All Commercial Banks
69	TOTLLNSA	Loans and Leases in Bank Credit, All Commercial Banks
72	TOTCINSA	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
73	SRPSABSNNCB	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
74	ASTLL	All sectors; total loans; liability, Level (NSA)
75	FBDILNECA	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
76	ASOLAL	All sectors; other loans and advances; liability, Level (NSA)
77	ASTMA	All sectors; total mortgages; asset, Level (NSA)
78	ASHMA	All sectors; home mortgages; asset, Level (NSA)
79	ASMRMA	All sectors; multifamily residential mortgages; asset, Level (NSA)
80	ASCMA	All sectors; commercial mortgages; asset, Level (NSA)
81	ASFMA	All sectors; farm mortgages; asset, Level (NSA)
82	CCLBSHNO	Households and nonprofit organizations; consumer credit; liability, Level (NSA)
83	FBDSILQ027S	Domestic financial sectors debt securities; liability, Level (NSA)
84	FBLL	Domestic financial sectors loans; liability, Level (NSA)
85	NCBDBIQ027S	Nonfinancial corporate business; debt securities; liability, Level
92	TB3MS	3-Month Treasury Bill: Secondary Market Rate (Monthly)
97	NEWORDER	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
109	GDP	Gross Domestic Product
110	FNDEFX	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
114	GDPDEF	Gross Domestic Product: Implicit Price Deflator
116	WLRRAL	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
117	FEDFUNDS	Effective Federal Funds Rate
118	GPDI	Gross Private Domestic Investment
120	MZMV	Velocity of MZM Money Stock
121	M1	M1 Money Stock
122	M2	M2 Money Stock
124	IPMAN	Industrial Production: Manufacturing (NAICS)
126	GS5	5-Year Treasury Constant Maturity Rate
131	GFDEBTN	Federal Debt: Total Public Debt
134	MSPUS	Median Sales Price of Houses Sold for the United States (NSA)
136	DGORDER	Manufacturers’ New Orders: Durable Goods (SA)
137	CSUSHPINSA	S&P/Case-Shiller U.S. National Home Price Index (NSA)
138	GFDEGDQ188S	Federal Debt: Total Public Debt as Percent of Gross Domestic Product
139	FYFSD	Federal Surplus or Deficit
140	FYFSGDA188S	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
145	OUTMS	Manufacturing Sector: Real Output
146	MANEMP	All Employees: Manufacturing
149	AAA	Moody’s Seasoned Aaa Corporate Bond Yield
152	SOFR99	Secured Overnight Financing Rate: 99th Percentile
156	OBFR	Overnight Bank Funding Rate
157	OBFR99	Overnight Bank Funding Rate: 99th Percentile
158	OBFR75	Overnight Bank Funding Rate: 75th Percentile
162	IOER	Interest Rate on Excess Reserves
164	EXCSRESNW	Excess Reserves of Depository Institutions
165	ECBASSETS	Central Bank Assets for Euro Area (11-19 Countries)
166	EUNNGDP	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
167	CEU0600000007	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
168	CURRENCY	Currency Component of M1 (Seasonally Adjusted)
169	WCURRNS	Currency Component of M1
172	PPIACO	Producer Price Index for All Commodities
173	PCUOMFGOMFG	Producer Price Index by Industry: Total Manufacturing Industries
174	POPTHM	Population (U.S.)
175	POPTHM	Population (U.S.)
181	FRGSHPUSM649NCIS	Cass Freight Index: Shipments
183	TERMCBPER24NS	Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
184	A065RC1A027NBEA	Personal income (NSA)
185	PI	Personal income (SA)
186	PCE	Personal Consumption Expenditures (SA)
187	A053RC1Q027SBEA	National income: Corporate profits before tax (without IVA and CCAdj)
227	MULTPLSP500SALESQUARTER	S&P 500 TTM Sales (Not Inflation Adjusted)
228	MULTPLSP500DIVYIELDMONTH	S&P 500 Dividend Yield by Month
230	CHRISCMEHG1	Copper Futures, Continuous Contract #1 (HG1) (Front Month)
231	WWDIWLDISAIRGOODMTK1	Air transport, freight
234	PETA123600001M	U.S. Regular Gasoline Retail Sales by Refiners, Monthly
235	PETA143B00001M	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
237	TOTALOGNRPUSM	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
238	TOTALPANRPUSM	Crude Oil Rotary Rigs in Operation, Monthly
239	TOTALNGNRPUSM	Natural Gas Rotary Rigs in Operation, Monthly
240	BKRTotal	Total Rig Count
241	BKRGas	Gas Rig Count
242	BKROil	Oil Rig Count
243	FARMINCOME	Net Farm Income
244	OPEARNINGSPERSHARE	Operating Earnings per Share
245	AREARNINGSPERSHARE	As-Reported Earnings per Share
246	CASHDIVIDENDSPERSHR	Cash Dividends per Share
247	SALESPERSHR	Sales per Share
248	BOOKVALPERSHR	Book value per Share
249	CAPEXPERSHR	Cap ex per Share
250	PRICE	Price
251	OPEARNINGSTTM	TTM Operating Earnings
252	AREARNINGSTTM	TTM Reported Earnings
253	FINRAMarginDebt	Margin Debt
254	FINRAFreeCreditMargin	Free Credit Balances in Customers’ Securities Margin Accounts
255	OCCEquityVolume	Equity Options Volume
256	OCCNonEquityVolume	Non-Equity Options Volume
260	BUSLOANS.by.GDP	Business Loans Normalized by GDP
263	BUSLOANSNSA.by.GDP	Business Loans Normalized by GDP
264	TOTCI.by.GDP	Business Loans (Weekly, SA) Normalized by GDP
265	TOTCINSA.by.GDP	Business Loans (Weekly, NSA) Normalized by GDP
268	W875RX1.by.GDP	Real Personal Income Normalized by GDP
270	PI.by.GDP	Personal Income (SA) Normalized by GDP
271	A053RC1Q027SBEA.by.GDP	National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
273	CONSUMERNSA.by.GDP	Consumer Loans Not Seasonally Adjusted divided by GDP
274	RREACBM027NBOG.by.GDP	Residental Real Estate Loans (Monthly, NSA) divided by GDP
275	RREACBM027SBOG.by.GDP	Residental Real Estate Loans (Monthly, SA) divided by GDP
276	RREACBW027SBOG.by.GDP	Residental Real Estate Loans (Weekly, SA) divided by GDP
277	RREACBW027NBOG.by.GDP	Residental Real Estate Loans (Weekly, NSA) divided by GDP
279	DGORDER.by.GDP	Durable Goods (Monthly, NSA) divided by GDP
280	ASHMA.by.GDP	Home Mortgages (Quarterly, NSA) divided by GDP
281	ASHMA.INTEREST	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
282	ASHMA.INTEREST.by.GDP	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
283	CONSUMERNSA.INTEREST	Consumer Loans (Not Seasonally Adjusted) Interest Burdens
284	CONSUMERNSA.INTEREST.by.GDP	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
285	TOTLNNSA	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
286	TOTLNNSA.by.GDP	Total Loans Not Seasonally Adjusted divided by GDP
291	WLRRAL.by.GDP	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
293	EXPCH.minus.IMPCH	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
295	SRPSABSNNCB.by.GDP	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
296	ASTLL.by.GDP	All sectors; total loans; liability, Level (NSA) Divided by GDP
299	ASFMA.INTEREST	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
300	ASFMA.INTEREST.by.GDP	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
313	NPPTTLBYPOPTHM	ADP Private Employment / Population
314	U6toU3	U6RATE minums UNRATE
324	GSG.Close.by.GSPC.Close	GSCI Commodity-Indexed Trust, Normalized by S&P 500
333	HNFSUSNSA.minus.HSN1FNSA	Houses for sale - houses sold
335	MSPUS.times.HNFSUSNSA	New privately owned 1-family units for sale times median price
341	CPIAUCSL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
343	CPIAUCSL_SmoothDer	Derivative of Smoothed Consumer Price Index for All Urban Consumers: All Items
344	CPIAUCSL_Log	Log of Consumer Price Index for All Urban Consumers: All Items
345	CPIAUCSL_mva200	Consumer Price Index for All Urban Consumers: All Items 200 Day MA
346	CPIAUCSL_mva050	Consumer Price Index for All Urban Consumers: All Items 50 Day MA
347	USREC_YoY	NBER based Recession Indicators Year over Year
348	USREC_YoY4	NBER based Recession Indicators 4 Year over 4 Year
349	USREC_YoY5	NBER based Recession Indicators 5 Year over 5 Year
350	USREC_Smooth	Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
351	USREC_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
352	USREC_SmoothDer	Derivative of Smoothed NBER based Recession Indicators
353	USREC_Log	Log of NBER based Recession Indicators
354	USREC_mva200	NBER based Recession Indicators 200 Day MA
355	USREC_mva050	NBER based Recession Indicators 50 Day MA
356	UNRATE_YoY	Civilian Unemployment Rate U-3 Year over Year
361	UNRATE_SmoothDer	Derivative of Smoothed Civilian Unemployment Rate U-3
371	PCEPI_Log	Log of Personal Consumption Expenditures: Chain-type Price Index
372	PCEPI_mva200	Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
373	PCEPI_mva050	Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
374	CCSA_YoY	Continued Claims (Insured Unemployment) Year over Year
379	CCSA_SmoothDer	Derivative of Smoothed Continued Claims (Insured Unemployment)
398	NPPTTL_Log	Log of Total Nonfarm Private Payroll Employment (ADP)
399	NPPTTL_mva200	Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
400	NPPTTL_mva050	Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
401	U6RATE_YoY	Total unemployed + margin + part-time U-6 Year over Year
402	U6RATE_YoY4	Total unemployed + margin + part-time U-6 4 Year over 4 Year
403	U6RATE_YoY5	Total unemployed + margin + part-time U-6 5 Year over 5 Year
406	U6RATE_SmoothDer	Derivative of Smoothed Total unemployed + margin + part-time U-6
413	PAYNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All Employees: Total Nonfarm Payrolls (NSA)
415	PAYNSA_SmoothDer	Derivative of Smoothed All Employees: Total Nonfarm Payrolls (NSA)
416	PAYNSA_Log	Log of All Employees: Total Nonfarm Payrolls (NSA)
417	PAYNSA_mva200	All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
418	PAYNSA_mva050	All Employees: Total Nonfarm Payrolls (NSA) 50 Day MA
422	TABSHNO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Households and nonprofit organizations; total assets, Level
431	HNONWPDPI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Household Net Worth, percent Dispsable Income
433	HNONWPDPI_SmoothDer	Derivative of Smoothed Household Net Worth, percent Dispsable Income
442	INDPRO_SmoothDer	Derivative of Smoothed Industrial Production Index
443	INDPRO_Log	Log of Industrial Production Index
444	INDPRO_mva200	Industrial Production Index 200 Day MA
445	INDPRO_mva050	Industrial Production Index 50 Day MA
451	RRSFS_SmoothDer	Derivative of Smoothed Real Retail and Food Services Sales
453	RRSFS_mva200	Real Retail and Food Services Sales 200 Day MA
455	RSALES_YoY	Real Retail Sales (DISCONTINUED) Year over Year
456	RSALES_YoY4	Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
457	RSALES_YoY5	Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
461	RSALES_Log	Log of Real Retail Sales (DISCONTINUED)
462	RSALES_mva200	Real Retail Sales (DISCONTINUED) 200 Day MA
463	RSALES_mva050	Real Retail Sales (DISCONTINUED) 50 Day MA
467	W875RX1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real personal income excluding current transfer receipts
470	W875RX1_Log	Log of Real personal income excluding current transfer receipts
471	W875RX1_mva200	Real personal income excluding current transfer receipts 200 Day MA
472	W875RX1_mva050	Real personal income excluding current transfer receipts 50 Day MA
483	PCOPPUSDM_YoY4	Global price of Copper 4 Year over 4 Year
487	PCOPPUSDM_SmoothDer	Derivative of Smoothed Global price of Copper
488	PCOPPUSDM_Log	Log of Global price of Copper
534	NOBL.Volume_mva200	200 Day MA
588	SCHD.Volume_mva200	200 Day MA
658	HPI.Open_SmoothDer	Derivative of Smoothed
667	HPI.High_SmoothDer	Derivative of Smoothed
676	HPI.Low_SmoothDer	Derivative of Smoothed
685	HPI.Close_SmoothDer	Derivative of Smoothed
696	HPI.Volume_mva200	200 Day MA
703	HPI.Adjusted_SmoothDer	Derivative of Smoothed
743	GSFTX.Volume_YoY	Year over Year
744	GSFTX.Volume_YoY4	4 Year over 4 Year
745	GSFTX.Volume_YoY5	5 Year over 5 Year
746	GSFTX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
747	GSFTX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
748	GSFTX.Volume_SmoothDer	Derivative of Smoothed
749	GSFTX.Volume_Log	Log of
750	GSFTX.Volume_mva200	200 Day MA
751	GSFTX.Volume_mva050	50 Day MA
764	LFMIX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
766	LFMIX.Open_SmoothDer	Derivative of Smoothed
769	LFMIX.Open_mva050	50 Day MA
773	LFMIX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
775	LFMIX.High_SmoothDer	Derivative of Smoothed
778	LFMIX.High_mva050	50 Day MA
782	LFMIX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
784	LFMIX.Low_SmoothDer	Derivative of Smoothed
787	LFMIX.Low_mva050	50 Day MA
791	LFMIX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
793	LFMIX.Close_SmoothDer	Derivative of Smoothed
796	LFMIX.Close_mva050	50 Day MA
797	LFMIX.Volume_YoY	Year over Year
798	LFMIX.Volume_YoY4	4 Year over 4 Year
799	LFMIX.Volume_YoY5	5 Year over 5 Year
800	LFMIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
801	LFMIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
802	LFMIX.Volume_SmoothDer	Derivative of Smoothed
803	LFMIX.Volume_Log	Log of
804	LFMIX.Volume_mva200	200 Day MA
805	LFMIX.Volume_mva050	50 Day MA
809	LFMIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
811	LFMIX.Adjusted_SmoothDer	Derivative of Smoothed
813	LFMIX.Adjusted_mva200	200 Day MA
814	LFMIX.Adjusted_mva050	50 Day MA
818	LFMCX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
820	LFMCX.Open_SmoothDer	Derivative of Smoothed
823	LFMCX.Open_mva050	50 Day MA
827	LFMCX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
829	LFMCX.High_SmoothDer	Derivative of Smoothed
832	LFMCX.High_mva050	50 Day MA
836	LFMCX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
838	LFMCX.Low_SmoothDer	Derivative of Smoothed
841	LFMCX.Low_mva050	50 Day MA
845	LFMCX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
847	LFMCX.Close_SmoothDer	Derivative of Smoothed
850	LFMCX.Close_mva050	50 Day MA
851	LFMCX.Volume_YoY	Year over Year
852	LFMCX.Volume_YoY4	4 Year over 4 Year
853	LFMCX.Volume_YoY5	5 Year over 5 Year
854	LFMCX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
855	LFMCX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
856	LFMCX.Volume_SmoothDer	Derivative of Smoothed
857	LFMCX.Volume_Log	Log of
858	LFMCX.Volume_mva200	200 Day MA
859	LFMCX.Volume_mva050	50 Day MA
863	LFMCX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
865	LFMCX.Adjusted_SmoothDer	Derivative of Smoothed
867	LFMCX.Adjusted_mva200	200 Day MA
868	LFMCX.Adjusted_mva050	50 Day MA
872	LFMAX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
874	LFMAX.Open_SmoothDer	Derivative of Smoothed
877	LFMAX.Open_mva050	50 Day MA
881	LFMAX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
883	LFMAX.High_SmoothDer	Derivative of Smoothed
886	LFMAX.High_mva050	50 Day MA
890	LFMAX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
892	LFMAX.Low_SmoothDer	Derivative of Smoothed
895	LFMAX.Low_mva050	50 Day MA
899	LFMAX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
901	LFMAX.Close_SmoothDer	Derivative of Smoothed
904	LFMAX.Close_mva050	50 Day MA
905	LFMAX.Volume_YoY	Year over Year
906	LFMAX.Volume_YoY4	4 Year over 4 Year
907	LFMAX.Volume_YoY5	5 Year over 5 Year
908	LFMAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
909	LFMAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
910	LFMAX.Volume_SmoothDer	Derivative of Smoothed
911	LFMAX.Volume_Log	Log of
912	LFMAX.Volume_mva200	200 Day MA
913	LFMAX.Volume_mva050	50 Day MA
917	LFMAX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
919	LFMAX.Adjusted_SmoothDer	Derivative of Smoothed
921	LFMAX.Adjusted_mva200	200 Day MA
922	LFMAX.Adjusted_mva050	50 Day MA
926	LCSIX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
928	LCSIX.Open_SmoothDer	Derivative of Smoothed
935	LCSIX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
937	LCSIX.High_SmoothDer	Derivative of Smoothed
944	LCSIX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
946	LCSIX.Low_SmoothDer	Derivative of Smoothed
953	LCSIX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
955	LCSIX.Close_SmoothDer	Derivative of Smoothed
959	LCSIX.Volume_YoY	Year over Year
960	LCSIX.Volume_YoY4	4 Year over 4 Year
961	LCSIX.Volume_YoY5	5 Year over 5 Year
962	LCSIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
963	LCSIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
964	LCSIX.Volume_SmoothDer	Derivative of Smoothed
965	LCSIX.Volume_Log	Log of
966	LCSIX.Volume_mva200	200 Day MA
967	LCSIX.Volume_mva050	50 Day MA
971	LCSIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
975	LCSIX.Adjusted_mva200	200 Day MA
1018	BSV.Volume_SmoothDer	Derivative of Smoothed
1020	BSV.Volume_mva200	200 Day MA
1067	VBIRX.Volume_YoY	Year over Year
1068	VBIRX.Volume_YoY4	4 Year over 4 Year
1069	VBIRX.Volume_YoY5	5 Year over 5 Year
1070	VBIRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1071	VBIRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1072	VBIRX.Volume_SmoothDer	Derivative of Smoothed
1073	VBIRX.Volume_Log	Log of
1074	VBIRX.Volume_mva200	200 Day MA
1075	VBIRX.Volume_mva050	50 Day MA
1175	VFSUX.Volume_YoY	Year over Year
1176	VFSUX.Volume_YoY4	4 Year over 4 Year
1177	VFSUX.Volume_YoY5	5 Year over 5 Year
1178	VFSUX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1179	VFSUX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1180	VFSUX.Volume_SmoothDer	Derivative of Smoothed
1181	VFSUX.Volume_Log	Log of
1182	VFSUX.Volume_mva200	200 Day MA
1183	VFSUX.Volume_mva050	50 Day MA
1229	LTUIX.Volume_YoY	Year over Year
1230	LTUIX.Volume_YoY4	4 Year over 4 Year
1231	LTUIX.Volume_YoY5	5 Year over 5 Year
1232	LTUIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1233	LTUIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1234	LTUIX.Volume_SmoothDer	Derivative of Smoothed
1235	LTUIX.Volume_Log	Log of
1236	LTUIX.Volume_mva200	200 Day MA
1237	LTUIX.Volume_mva050	50 Day MA
1283	PTTPX.Volume_YoY	Year over Year
1284	PTTPX.Volume_YoY4	4 Year over 4 Year
1285	PTTPX.Volume_YoY5	5 Year over 5 Year
1286	PTTPX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1287	PTTPX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1288	PTTPX.Volume_SmoothDer	Derivative of Smoothed
1289	PTTPX.Volume_Log	Log of
1290	PTTPX.Volume_mva200	200 Day MA
1291	PTTPX.Volume_mva050	50 Day MA
1337	NERYX.Volume_YoY	Year over Year
1338	NERYX.Volume_YoY4	4 Year over 4 Year
1339	NERYX.Volume_YoY5	5 Year over 5 Year
1340	NERYX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1341	NERYX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1342	NERYX.Volume_SmoothDer	Derivative of Smoothed
1343	NERYX.Volume_Log	Log of
1344	NERYX.Volume_mva200	200 Day MA
1345	NERYX.Volume_mva050	50 Day MA
1391	STIGX.Volume_YoY	Year over Year
1392	STIGX.Volume_YoY4	4 Year over 4 Year
1393	STIGX.Volume_YoY5	5 Year over 5 Year
1394	STIGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1395	STIGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1396	STIGX.Volume_SmoothDer	Derivative of Smoothed
1397	STIGX.Volume_Log	Log of
1398	STIGX.Volume_mva200	200 Day MA
1399	STIGX.Volume_mva050	50 Day MA
1445	HLGAX.Volume_YoY	Year over Year
1446	HLGAX.Volume_YoY4	4 Year over 4 Year
1447	HLGAX.Volume_YoY5	5 Year over 5 Year
1448	HLGAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1449	HLGAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1450	HLGAX.Volume_SmoothDer	Derivative of Smoothed
1451	HLGAX.Volume_Log	Log of
1452	HLGAX.Volume_mva200	200 Day MA
1453	HLGAX.Volume_mva050	50 Day MA
1499	FTRGX.Volume_YoY	Year over Year
1500	FTRGX.Volume_YoY4	4 Year over 4 Year
1501	FTRGX.Volume_YoY5	5 Year over 5 Year
1502	FTRGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1503	FTRGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1504	FTRGX.Volume_SmoothDer	Derivative of Smoothed
1505	FTRGX.Volume_Log	Log of
1506	FTRGX.Volume_mva200	200 Day MA
1507	FTRGX.Volume_mva050	50 Day MA
1553	THIIX.Volume_YoY	Year over Year
1554	THIIX.Volume_YoY4	4 Year over 4 Year
1555	THIIX.Volume_YoY5	5 Year over 5 Year
1556	THIIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1557	THIIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1558	THIIX.Volume_SmoothDer	Derivative of Smoothed
1559	THIIX.Volume_Log	Log of
1560	THIIX.Volume_mva200	200 Day MA
1561	THIIX.Volume_mva050	50 Day MA
1607	PTTRX.Volume_YoY	Year over Year
1608	PTTRX.Volume_YoY4	4 Year over 4 Year
1609	PTTRX.Volume_YoY5	5 Year over 5 Year
1610	PTTRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1611	PTTRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1612	PTTRX.Volume_SmoothDer	Derivative of Smoothed
1613	PTTRX.Volume_Log	Log of
1614	PTTRX.Volume_mva200	200 Day MA
1615	PTTRX.Volume_mva050	50 Day MA
1661	BFIGX.Volume_YoY	Year over Year
1662	BFIGX.Volume_YoY4	4 Year over 4 Year
1663	BFIGX.Volume_YoY5	5 Year over 5 Year
1664	BFIGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1665	BFIGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1666	BFIGX.Volume_SmoothDer	Derivative of Smoothed
1667	BFIGX.Volume_Log	Log of
1668	BFIGX.Volume_mva200	200 Day MA
1669	BFIGX.Volume_mva050	50 Day MA
1769	EIFAX.Volume_YoY	Year over Year
1770	EIFAX.Volume_YoY4	4 Year over 4 Year
1771	EIFAX.Volume_YoY5	5 Year over 5 Year
1772	EIFAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1773	EIFAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1774	EIFAX.Volume_SmoothDer	Derivative of Smoothed
1775	EIFAX.Volume_Log	Log of
1776	EIFAX.Volume_mva200	200 Day MA
1777	EIFAX.Volume_mva050	50 Day MA
1823	ASDAX.Volume_YoY	Year over Year
1824	ASDAX.Volume_YoY4	4 Year over 4 Year
1825	ASDAX.Volume_YoY5	5 Year over 5 Year
1826	ASDAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1827	ASDAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1828	ASDAX.Volume_SmoothDer	Derivative of Smoothed
1829	ASDAX.Volume_Log	Log of
1830	ASDAX.Volume_mva200	200 Day MA
1831	ASDAX.Volume_mva050	50 Day MA
1877	TRBUX.Volume_YoY	Year over Year
1878	TRBUX.Volume_YoY4	4 Year over 4 Year
1879	TRBUX.Volume_YoY5	5 Year over 5 Year
1880	TRBUX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1881	TRBUX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1882	TRBUX.Volume_SmoothDer	Derivative of Smoothed
1883	TRBUX.Volume_Log	Log of
1884	TRBUX.Volume_mva200	200 Day MA
1885	TRBUX.Volume_mva050	50 Day MA
1931	PRVIX.Volume_YoY	Year over Year
1932	PRVIX.Volume_YoY4	4 Year over 4 Year
1933	PRVIX.Volume_YoY5	5 Year over 5 Year
1934	PRVIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1935	PRVIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1936	PRVIX.Volume_SmoothDer	Derivative of Smoothed
1937	PRVIX.Volume_Log	Log of
1938	PRVIX.Volume_mva200	200 Day MA
1939	PRVIX.Volume_mva050	50 Day MA
1985	PRWCX.Volume_YoY	Year over Year
1986	PRWCX.Volume_YoY4	4 Year over 4 Year
1987	PRWCX.Volume_YoY5	5 Year over 5 Year
1988	PRWCX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1989	PRWCX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1990	PRWCX.Volume_SmoothDer	Derivative of Smoothed
1991	PRWCX.Volume_Log	Log of
1992	PRWCX.Volume_mva200	200 Day MA
1993	PRWCX.Volume_mva050	50 Day MA
2039	ADOZX.Volume_YoY	Year over Year
2040	ADOZX.Volume_YoY4	4 Year over 4 Year
2041	ADOZX.Volume_YoY5	5 Year over 5 Year
2042	ADOZX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2043	ADOZX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2044	ADOZX.Volume_SmoothDer	Derivative of Smoothed
2045	ADOZX.Volume_Log	Log of
2046	ADOZX.Volume_mva200	200 Day MA
2047	ADOZX.Volume_mva050	50 Day MA
2062	MERFX.Open_SmoothDer	Derivative of Smoothed
2071	MERFX.High_SmoothDer	Derivative of Smoothed
2080	MERFX.Low_SmoothDer	Derivative of Smoothed
2089	MERFX.Close_SmoothDer	Derivative of Smoothed
2093	MERFX.Volume_YoY	Year over Year
2094	MERFX.Volume_YoY4	4 Year over 4 Year
2095	MERFX.Volume_YoY5	5 Year over 5 Year
2096	MERFX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2097	MERFX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2098	MERFX.Volume_SmoothDer	Derivative of Smoothed
2099	MERFX.Volume_Log	Log of
2100	MERFX.Volume_mva200	200 Day MA
2101	MERFX.Volume_mva050	50 Day MA
2107	MERFX.Adjusted_SmoothDer	Derivative of Smoothed
2147	CMNIX.Volume_YoY	Year over Year
2148	CMNIX.Volume_YoY4	4 Year over 4 Year
2149	CMNIX.Volume_YoY5	5 Year over 5 Year
2150	CMNIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2151	CMNIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2152	CMNIX.Volume_SmoothDer	Derivative of Smoothed
2153	CMNIX.Volume_Log	Log of
2154	CMNIX.Volume_mva200	200 Day MA
2155	CMNIX.Volume_mva050	50 Day MA
2201	CIHEX.Volume_YoY	Year over Year
2202	CIHEX.Volume_YoY4	4 Year over 4 Year
2203	CIHEX.Volume_YoY5	5 Year over 5 Year
2204	CIHEX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2205	CIHEX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2206	CIHEX.Volume_SmoothDer	Derivative of Smoothed
2207	CIHEX.Volume_Log	Log of
2208	CIHEX.Volume_mva200	200 Day MA
2209	CIHEX.Volume_mva050	50 Day MA
2240	IMPMX_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2242	IMPMX_SmoothDer	Derivative of Smoothed U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2244	IMPMX_mva200	U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 200 Day MA
2249	EXPMX_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2251	EXPMX_SmoothDer	Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2253	EXPMX_mva200	U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 200 Day MA
2267	HNFSUSNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses for Sale in the United States (Monthly, NSA)
2269	HNFSUSNSA_SmoothDer	Derivative of Smoothed New One Family Houses for Sale in the United States (Monthly, NSA)
2270	HNFSUSNSA_Log	Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2271	HNFSUSNSA_mva200	New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2272	HNFSUSNSA_mva050	New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2273	BUSLOANS_YoY	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) Year over Year
2276	BUSLOANS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2278	BUSLOANS_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2279	BUSLOANS_Log	Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2280	BUSLOANS_mva200	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2281	BUSLOANS_mva050	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2282	TOTCI_YoY	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) Year over Year
2285	TOTCI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2287	TOTCI_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2288	TOTCI_Log	Log of Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2289	TOTCI_mva200	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2290	TOTCI_mva050	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2291	BUSLOANSNSA_YoY	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) Year over Year
2293	BUSLOANSNSA_YoY5	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 5 Year over 5 Year
2294	BUSLOANSNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2296	BUSLOANSNSA_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2297	BUSLOANSNSA_Log	Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2298	BUSLOANSNSA_mva200	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2299	BUSLOANSNSA_mva050	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2303	REALLNNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, NSA)
2306	REALLNNSA_Log	Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2307	REALLNNSA_mva200	Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2308	REALLNNSA_mva050	Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2312	REALLN_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2314	REALLN_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Monthly, SA)
2315	REALLN_Log	Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2316	REALLN_mva200	Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2317	REALLN_mva050	Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2321	RELACBW027NBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, NSA)
2323	RELACBW027NBOG_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, NSA)
2324	RELACBW027NBOG_Log	Log of Real Estate Loans, All Commercial Banks (Weekly, NSA)
2325	RELACBW027NBOG_mva200	Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2326	RELACBW027NBOG_mva050	Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2330	RELACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2332	RELACBW027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2333	RELACBW027SBOG_Log	Log of Real Estate Loans, All Commercial Banks (Weekly, SA)
2334	RELACBW027SBOG_mva200	Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2335	RELACBW027SBOG_mva050	Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2339	RREACBM027NBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2342	RREACBM027NBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2343	RREACBM027NBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2344	RREACBM027NBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2348	RREACBM027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2350	RREACBM027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2351	RREACBM027SBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2352	RREACBM027SBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2353	RREACBM027SBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2357	RREACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2359	RREACBW027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2360	RREACBW027SBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2361	RREACBW027SBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2362	RREACBW027SBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2365	RREACBW027NBOG_YoY5	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 5 Year over 5 Year
2366	RREACBW027NBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2369	RREACBW027NBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2370	RREACBW027NBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2371	RREACBW027NBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2372	MORTGAGE30US_YoY	30-Year Fixed Rate Mortgage Average in the United States Year over Year
2373	MORTGAGE30US_YoY4	30-Year Fixed Rate Mortgage Average in the United States 4 Year over 4 Year
2374	MORTGAGE30US_YoY5	30-Year Fixed Rate Mortgage Average in the United States 5 Year over 5 Year
2375	MORTGAGE30US_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2376	MORTGAGE30US_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 30-Year Fixed Rate Mortgage Average in the United States
2377	MORTGAGE30US_SmoothDer	Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2378	MORTGAGE30US_Log	Log of 30-Year Fixed Rate Mortgage Average in the United States
2379	MORTGAGE30US_mva200	30-Year Fixed Rate Mortgage Average in the United States 200 Day MA
2380	MORTGAGE30US_mva050	30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2384	CONSUMERNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans, All Commercial Banks
2387	CONSUMERNSA_Log	Log of Consumer Loans, All Commercial Banks
2388	CONSUMERNSA_mva200	Consumer Loans, All Commercial Banks 200 Day MA
2389	CONSUMERNSA_mva050	Consumer Loans, All Commercial Banks 50 Day MA
2390	TOTLLNSA_YoY	Loans and Leases in Bank Credit, All Commercial Banks Year over Year
2393	TOTLLNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2395	TOTLLNSA_SmoothDer	Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2396	TOTLLNSA_Log	Log of Loans and Leases in Bank Credit, All Commercial Banks
2397	TOTLLNSA_mva200	Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2398	TOTLLNSA_mva050	Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2406	DPSACBW027SBOG_mva200	Deposits, All Commercial Banks 200 Day MA
2411	DRCLACBS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2417	TOTCINSA_YoY	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) Year over Year
2420	TOTCINSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2422	TOTCINSA_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2423	TOTCINSA_Log	Log of Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2424	TOTCINSA_mva200	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2425	TOTCINSA_mva050	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2427	SRPSABSNNCB_YoY4	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 4 Year over 4 Year
2428	SRPSABSNNCB_YoY5	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 5 Year over 5 Year
2432	SRPSABSNNCB_Log	Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2433	SRPSABSNNCB_mva200	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 200 Day MA
2434	SRPSABSNNCB_mva050	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2441	ASTLL_Log	Log of All sectors; total loans; liability, Level (NSA)
2442	ASTLL_mva200	All sectors; total loans; liability, Level (NSA) 200 Day MA
2443	ASTLL_mva050	All sectors; total loans; liability, Level (NSA) 50 Day MA
2444	FBDILNECA_YoY	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) Year over Year
2450	FBDILNECA_Log	Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2451	FBDILNECA_mva200	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 200 Day MA
2452	FBDILNECA_mva050	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA) 50 Day MA
2459	ASOLAL_Log	Log of All sectors; other loans and advances; liability, Level (NSA)
2460	ASOLAL_mva200	All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2461	ASOLAL_mva050	All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2468	ASTMA_Log	Log of All sectors; total mortgages; asset, Level (NSA)
2469	ASTMA_mva200	All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2470	ASTMA_mva050	All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2477	ASHMA_Log	Log of All sectors; home mortgages; asset, Level (NSA)
2478	ASHMA_mva200	All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2479	ASHMA_mva050	All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2486	ASMRMA_Log	Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2487	ASMRMA_mva200	All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2488	ASMRMA_mva050	All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2495	ASCMA_Log	Log of All sectors; commercial mortgages; asset, Level (NSA)
2496	ASCMA_mva200	All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2497	ASCMA_mva050	All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2504	ASFMA_Log	Log of All sectors; farm mortgages; asset, Level (NSA)
2505	ASFMA_mva200	All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2506	ASFMA_mva050	All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2513	CCLBSHNO_Log	Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2514	CCLBSHNO_mva200	Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2515	CCLBSHNO_mva050	Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2522	FBDSILQ027S_Log	Log of Domestic financial sectors debt securities; liability, Level (NSA)
2523	FBDSILQ027S_mva200	Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2524	FBDSILQ027S_mva050	Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2526	FBLL_YoY4	Domestic financial sectors loans; liability, Level (NSA) 4 Year over 4 Year
2531	FBLL_Log	Log of Domestic financial sectors loans; liability, Level (NSA)
2532	FBLL_mva200	Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2533	FBLL_mva050	Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2540	NCBDBIQ027S_Log	Log of Nonfinancial corporate business; debt securities; liability, Level
2541	NCBDBIQ027S_mva200	Nonfinancial corporate business; debt securities; liability, Level 200 Day MA
2542	NCBDBIQ027S_mva050	Nonfinancial corporate business; debt securities; liability, Level 50 Day MA
2546	DGS10_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2548	DGS10_SmoothDer	Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2550	DGS10_mva200	10-Year Treasury Constant Maturity Rate 200 Day MA
2551	DGS10_mva050	10-Year Treasury Constant Maturity Rate 50 Day MA
2552	TNX.Open_YoY	Year over Year
2553	TNX.Open_YoY4	4 Year over 4 Year
2554	TNX.Open_YoY5	5 Year over 5 Year
2555	TNX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2556	TNX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2557	TNX.Open_SmoothDer	Derivative of Smoothed
2558	TNX.Open_Log	Log of
2559	TNX.Open_mva200	200 Day MA
2560	TNX.Open_mva050	50 Day MA
2564	TNX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2565	TNX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2566	TNX.High_SmoothDer	Derivative of Smoothed
2568	TNX.High_mva200	200 Day MA
2569	TNX.High_mva050	50 Day MA
2573	TNX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2574	TNX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2575	TNX.Low_SmoothDer	Derivative of Smoothed
2577	TNX.Low_mva200	200 Day MA
2578	TNX.Low_mva050	50 Day MA
2582	TNX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2584	TNX.Close_SmoothDer	Derivative of Smoothed
2586	TNX.Close_mva200	200 Day MA
2587	TNX.Close_mva050	50 Day MA
2588	TNX.Volume_YoY	Year over Year
2589	TNX.Volume_YoY4	4 Year over 4 Year
2590	TNX.Volume_YoY5	5 Year over 5 Year
2591	TNX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2592	TNX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2593	TNX.Volume_SmoothDer	Derivative of Smoothed
2594	TNX.Volume_Log	Log of
2595	TNX.Volume_mva200	200 Day MA
2596	TNX.Volume_mva050	50 Day MA
2600	TNX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2602	TNX.Adjusted_SmoothDer	Derivative of Smoothed
2604	TNX.Adjusted_mva200	200 Day MA
2605	TNX.Adjusted_mva050	50 Day MA
2609	CLF.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2611	CLF.Open_SmoothDer	Derivative of Smoothed
2612	CLF.Open_Log	Log of
2613	CLF.Open_mva200	200 Day MA
2614	CLF.Open_mva050	50 Day MA
2618	CLF.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2620	CLF.High_SmoothDer	Derivative of Smoothed
2622	CLF.High_mva200	200 Day MA
2623	CLF.High_mva050	50 Day MA
2627	CLF.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2629	CLF.Low_SmoothDer	Derivative of Smoothed
2630	CLF.Low_Log	Log of
2631	CLF.Low_mva200	200 Day MA
2632	CLF.Low_mva050	50 Day MA
2636	CLF.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2638	CLF.Close_SmoothDer	Derivative of Smoothed
2639	CLF.Close_Log	Log of
2640	CLF.Close_mva200	200 Day MA
2641	CLF.Close_mva050	50 Day MA
2648	CLF.Volume_Log	Log of
2654	CLF.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2656	CLF.Adjusted_SmoothDer	Derivative of Smoothed
2657	CLF.Adjusted_Log	Log of
2658	CLF.Adjusted_mva200	200 Day MA
2659	CLF.Adjusted_mva050	50 Day MA
2663	DGS30_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2664	DGS30_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 10-Year Treasury Constant Maturity Rate
2665	DGS30_SmoothDer	Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2667	DGS30_mva200	10-Year Treasury Constant Maturity Rate 200 Day MA
2668	DGS30_mva050	10-Year Treasury Constant Maturity Rate 50 Day MA
2672	DGS1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2673	DGS1_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 1-Year Treasury Constant Maturity Rate
2674	DGS1_SmoothDer	Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2676	DGS1_mva200	1-Year Treasury Constant Maturity Rate 200 Day MA
2677	DGS1_mva050	1-Year Treasury Constant Maturity Rate 50 Day MA
2681	DGS2_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2683	DGS2_SmoothDer	Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2685	DGS2_mva200	2-Year Treasury Constant Maturity Rate 200 Day MA
2686	DGS2_mva050	2-Year Treasury Constant Maturity Rate 50 Day MA
2690	TB3MS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2692	TB3MS_SmoothDer	Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2693	TB3MS_Log	Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2694	TB3MS_mva200	3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2695	TB3MS_mva050	3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2699	DTB3_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2700	DTB3_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2701	DTB3_SmoothDer	Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2702	DTB3_Log	Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2703	DTB3_mva200	3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2704	DTB3_mva050	3-Month Treasury Bill: Secondary Market Rate (Daily) 50 Day MA
2708	IRX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2709	IRX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2711	IRX.Open_Log	Log of
2712	IRX.Open_mva200	200 Day MA
2713	IRX.Open_mva050	50 Day MA
2717	IRX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2718	IRX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2720	IRX.High_Log	Log of
2721	IRX.High_mva200	200 Day MA
2722	IRX.High_mva050	50 Day MA
2726	IRX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2727	IRX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2728	IRX.Low_SmoothDer	Derivative of Smoothed
2729	IRX.Low_Log	Log of
2730	IRX.Low_mva200	200 Day MA
2731	IRX.Low_mva050	50 Day MA
2735	IRX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2736	IRX.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2737	IRX.Close_SmoothDer	Derivative of Smoothed
2738	IRX.Close_Log	Log of
2739	IRX.Close_mva200	200 Day MA
2740	IRX.Close_mva050	50 Day MA
2741	IRX.Volume_YoY	Year over Year
2742	IRX.Volume_YoY4	4 Year over 4 Year
2743	IRX.Volume_YoY5	5 Year over 5 Year
2744	IRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2745	IRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2746	IRX.Volume_SmoothDer	Derivative of Smoothed
2747	IRX.Volume_Log	Log of
2748	IRX.Volume_mva200	200 Day MA
2749	IRX.Volume_mva050	50 Day MA
2753	IRX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2754	IRX.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2755	IRX.Adjusted_SmoothDer	Derivative of Smoothed
2756	IRX.Adjusted_Log	Log of
2757	IRX.Adjusted_mva200	200 Day MA
2758	IRX.Adjusted_mva050	50 Day MA
2762	DCOILWTICO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2764	DCOILWTICO_SmoothDer	Derivative of Smoothed Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2765	DCOILWTICO_Log	Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2766	DCOILWTICO_mva200	Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
2767	DCOILWTICO_mva050	Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 50 Day MA
2771	DCOILBRENTEU_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
2773	DCOILBRENTEU_SmoothDer	Derivative of Smoothed Crude Oil Prices: Brent - Europe
2775	DCOILBRENTEU_mva200	Crude Oil Prices: Brent - Europe 200 Day MA
2776	DCOILBRENTEU_mva050	Crude Oil Prices: Brent - Europe 50 Day MA
2783	NEWORDER_Log	Log of Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
2784	NEWORDER_mva200	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
2785	NEWORDER_mva050	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 50 Day MA
2798	ICSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Initial Jobless Claims
2800	ICSA_SmoothDer	Derivative of Smoothed Initial Jobless Claims
2847	GSPC.Volume_mva200	200 Day MA
2894	FXAIX.Volume_YoY	Year over Year
2895	FXAIX.Volume_YoY4	4 Year over 4 Year
2896	FXAIX.Volume_YoY5	5 Year over 5 Year
2897	FXAIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2898	FXAIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2899	FXAIX.Volume_SmoothDer	Derivative of Smoothed
2900	FXAIX.Volume_Log	Log of
2901	FXAIX.Volume_mva200	200 Day MA
2902	FXAIX.Volume_mva050	50 Day MA
2948	FTIHX.Volume_YoY	Year over Year
2949	FTIHX.Volume_YoY4	4 Year over 4 Year
2950	FTIHX.Volume_YoY5	5 Year over 5 Year
2951	FTIHX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2952	FTIHX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2953	FTIHX.Volume_SmoothDer	Derivative of Smoothed
2954	FTIHX.Volume_Log	Log of
2955	FTIHX.Volume_mva200	200 Day MA
2956	FTIHX.Volume_mva050	50 Day MA
3002	MDIZX.Volume_YoY	Year over Year
3003	MDIZX.Volume_YoY4	4 Year over 4 Year
3004	MDIZX.Volume_YoY5	5 Year over 5 Year
3005	MDIZX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3006	MDIZX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3007	MDIZX.Volume_SmoothDer	Derivative of Smoothed
3008	MDIZX.Volume_Log	Log of
3009	MDIZX.Volume_mva200	200 Day MA
3010	MDIZX.Volume_mva050	50 Day MA
3056	DODIX.Volume_YoY	Year over Year
3057	DODIX.Volume_YoY4	4 Year over 4 Year
3058	DODIX.Volume_YoY5	5 Year over 5 Year
3059	DODIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3060	DODIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3061	DODIX.Volume_SmoothDer	Derivative of Smoothed
3062	DODIX.Volume_Log	Log of
3063	DODIX.Volume_mva200	200 Day MA
3064	DODIX.Volume_mva050	50 Day MA
3110	RLG.Volume_YoY	Year over Year
3111	RLG.Volume_YoY4	4 Year over 4 Year
3112	RLG.Volume_YoY5	5 Year over 5 Year
3113	RLG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3114	RLG.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3115	RLG.Volume_SmoothDer	Derivative of Smoothed
3116	RLG.Volume_Log	Log of
3117	RLG.Volume_mva200	200 Day MA
3118	RLG.Volume_mva050	50 Day MA
3224	STOXX50E.Volume_Log	Log of
3279	EFA.Volume_mva200	200 Day MA
3296	GDP_Log	Log of Gross Domestic Product
3297	GDP_mva200	Gross Domestic Product 200 Day MA
3298	GDP_mva050	Gross Domestic Product 50 Day MA
3299	FNDEFX_YoY	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) Year over Year
3305	FNDEFX_Log	Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3306	FNDEFX_mva200	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3307	FNDEFX_mva050	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3313	FDEFX_SmoothDer	Derivative of Smoothed Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3323	GDPNOW_Log	Log of Fed Atlanta GDPNow
3341	GDPDEF_Log	Log of Gross Domestic Product: Implicit Price Deflator
3342	GDPDEF_mva200	Gross Domestic Product: Implicit Price Deflator 200 Day MA
3343	GDPDEF_mva050	Gross Domestic Product: Implicit Price Deflator 50 Day MA
3387	VIG.Volume_mva200	200 Day MA
3401	WLRRAL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3404	WLRRAL_Log	Log of Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3405	WLRRAL_mva200	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 200 Day MA
3406	WLRRAL_mva050	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 50 Day MA
3410	FEDFUNDS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Effective Federal Funds Rate
3412	FEDFUNDS_SmoothDer	Derivative of Smoothed Effective Federal Funds Rate
3413	FEDFUNDS_Log	Log of Effective Federal Funds Rate
3414	FEDFUNDS_mva200	Effective Federal Funds Rate 200 Day MA
3415	FEDFUNDS_mva050	Effective Federal Funds Rate 50 Day MA
3422	GPDI_Log	Log of Gross Private Domestic Investment
3423	GPDI_mva200	Gross Private Domestic Investment 200 Day MA
3424	GPDI_mva050	Gross Private Domestic Investment 50 Day MA
3428	W790RC1Q027SBEA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Net domestic investment: Private: Domestic busines
3431	W790RC1Q027SBEA_Log	Log of Net domestic investment: Private: Domestic busines
3434	MZMV_YoY	Velocity of MZM Money Stock Year over Year
3440	MZMV_Log	Log of Velocity of MZM Money Stock
3441	MZMV_mva200	Velocity of MZM Money Stock 200 Day MA
3442	MZMV_mva050	Velocity of MZM Money Stock 50 Day MA
3449	M1_Log	Log of M1 Money Stock
3450	M1_mva200	M1 Money Stock 200 Day MA
3451	M1_mva050	M1 Money Stock 50 Day MA
3458	M2_Log	Log of M2 Money Stock
3459	M2_mva200	M2 Money Stock 200 Day MA
3460	M2_mva050	M2 Money Stock 50 Day MA
3466	OPHNFB_SmoothDer	Derivative of Smoothed Nonfarm Business Sector: Real Output Per Hour of All Persons
3475	IPMAN_SmoothDer	Derivative of Smoothed Industrial Production: Manufacturing (NAICS)
3476	IPMAN_Log	Log of Industrial Production: Manufacturing (NAICS)
3477	IPMAN_mva200	Industrial Production: Manufacturing (NAICS) 200 Day MA
3478	IPMAN_mva050	Industrial Production: Manufacturing (NAICS) 50 Day MA
3533	GS5_YoY	5-Year Treasury Constant Maturity Rate Year over Year
3534	GS5_YoY4	5-Year Treasury Constant Maturity Rate 4 Year over 4 Year
3536	GS5_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3538	GS5_SmoothDer	Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3539	GS5_Log	Log of 5-Year Treasury Constant Maturity Rate
3540	GS5_mva200	5-Year Treasury Constant Maturity Rate 200 Day MA
3541	GS5_mva050	5-Year Treasury Constant Maturity Rate 50 Day MA
3554	VIXCLS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3558	VIXCLS_mva200	CBOE Volatility Index 200 Day MA
3563	VXX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3581	VXX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3590	VXX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3598	VXX.Volume_YoY5	5 Year over 5 Year
3602	VXX.Volume_Log	Log of
3608	VXX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3629	GFDEBTN_Log	Log of Federal Debt: Total Public Debt
3630	GFDEBTN_mva200	Federal Debt: Total Public Debt 200 Day MA
3631	GFDEBTN_mva050	Federal Debt: Total Public Debt 50 Day MA
3656	MSPUS_Log	Log of Median Sales Price of Houses Sold for the United States (NSA)
3657	MSPUS_mva200	Median Sales Price of Houses Sold for the United States (NSA) 200 Day MA
3658	MSPUS_mva050	Median Sales Price of Houses Sold for the United States (NSA) 50 Day MA
3674	DGORDER_Log	Log of Manufacturers’ New Orders: Durable Goods (SA)
3675	DGORDER_mva200	Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
3676	DGORDER_mva050	Manufacturers’ New Orders: Durable Goods (SA) 50 Day MA
3683	CSUSHPINSA_Log	Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
3684	CSUSHPINSA_mva200	S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
3685	CSUSHPINSA_mva050	S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
3686	GFDEGDQ188S_YoY	Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
3692	GFDEGDQ188S_Log	Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3693	GFDEGDQ188S_mva200	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 200 Day MA
3694	GFDEGDQ188S_mva050	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 50 Day MA
3695	FYFSD_YoY	Federal Surplus or Deficit Year over Year
3698	FYFSD_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Federal Surplus or Deficit
3699	FYFSD_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Federal Surplus or Deficit
3701	FYFSD_Log	Log of Federal Surplus or Deficit
3702	FYFSD_mva200	Federal Surplus or Deficit 200 Day MA
3703	FYFSD_mva050	Federal Surplus or Deficit 50 Day MA
3704	FYFSGDA188S_YoY	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
3710	FYFSGDA188S_Log	Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3711	FYFSGDA188S_mva200	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
3712	FYFSGDA188S_mva050	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
3718	GDX.Open_SmoothDer	Derivative of Smoothed
3727	GDX.High_SmoothDer	Derivative of Smoothed
3736	GDX.Low_SmoothDer	Derivative of Smoothed
3745	GDX.Close_SmoothDer	Derivative of Smoothed
3763	GDX.Adjusted_SmoothDer	Derivative of Smoothed
3770	XLE.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3772	XLE.Open_SmoothDer	Derivative of Smoothed
3774	XLE.Open_mva200	200 Day MA
3775	XLE.Open_mva050	50 Day MA
3779	XLE.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3781	XLE.High_SmoothDer	Derivative of Smoothed
3783	XLE.High_mva200	200 Day MA
3784	XLE.High_mva050	50 Day MA
3788	XLE.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3790	XLE.Low_SmoothDer	Derivative of Smoothed
3792	XLE.Low_mva200	200 Day MA
3793	XLE.Low_mva050	50 Day MA
3797	XLE.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3799	XLE.Close_SmoothDer	Derivative of Smoothed
3801	XLE.Close_mva200	200 Day MA
3802	XLE.Close_mva050	50 Day MA
3815	XLE.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3817	XLE.Adjusted_SmoothDer	Derivative of Smoothed
3819	XLE.Adjusted_mva200	200 Day MA
3820	XLE.Adjusted_mva050	50 Day MA
3824	GSG.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3826	GSG.Open_SmoothDer	Derivative of Smoothed
3828	GSG.Open_mva200	200 Day MA
3829	GSG.Open_mva050	50 Day MA
3833	GSG.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3835	GSG.High_SmoothDer	Derivative of Smoothed
3837	GSG.High_mva200	200 Day MA
3838	GSG.High_mva050	50 Day MA
3842	GSG.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3844	GSG.Low_SmoothDer	Derivative of Smoothed
3846	GSG.Low_mva200	200 Day MA
3847	GSG.Low_mva050	50 Day MA
3851	GSG.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3853	GSG.Close_SmoothDer	Derivative of Smoothed
3855	GSG.Close_mva200	200 Day MA
3856	GSG.Close_mva050	50 Day MA
3869	GSG.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3871	GSG.Adjusted_SmoothDer	Derivative of Smoothed
3873	GSG.Adjusted_mva200	200 Day MA
3874	GSG.Adjusted_mva050	50 Day MA
3876	WALCL_YoY4	All Federal Reserve Banks: Total Assets 4 Year over 4 Year
3882	WALCL_mva200	All Federal Reserve Banks: Total Assets 200 Day MA
3890	OUTMS_Log	Log of Manufacturing Sector: Real Output
3891	OUTMS_mva200	Manufacturing Sector: Real Output 200 Day MA
3892	OUTMS_mva050	Manufacturing Sector: Real Output 50 Day MA
3896	MANEMP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All Employees: Manufacturing
3899	MANEMP_Log	Log of All Employees: Manufacturing
3900	MANEMP_mva200	All Employees: Manufacturing 200 Day MA
3901	MANEMP_mva050	All Employees: Manufacturing 50 Day MA
3904	PRS30006163_YoY5	Manufacturing Sector: Real Output Per Person 5 Year over 5 Year
3907	PRS30006163_SmoothDer	Derivative of Smoothed Manufacturing Sector: Real Output Per Person
3914	BAMLC0A3CA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
3916	BAMLC0A3CA_SmoothDer	Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
3918	BAMLC0A3CA_mva200	ICE BofAML US Corporate A Option-Adjusted Spread 200 Day MA
3919	BAMLC0A3CA_mva050	ICE BofAML US Corporate A Option-Adjusted Spread 50 Day MA
3920	AAA_YoY	Moody’s Seasoned Aaa Corporate Bond Yield Year over Year
3921	AAA_YoY4	Moody’s Seasoned Aaa Corporate Bond Yield 4 Year over 4 Year
3923	AAA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
3925	AAA_SmoothDer	Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
3926	AAA_Log	Log of Moody’s Seasoned Aaa Corporate Bond Yield
3927	AAA_mva200	Moody’s Seasoned Aaa Corporate Bond Yield 200 Day MA
3928	AAA_mva050	Moody’s Seasoned Aaa Corporate Bond Yield 50 Day MA
3932	SOFR_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate
3934	SOFR_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate
3936	SOFR_mva200	Secured Overnight Financing Rate 200 Day MA
3937	SOFR_mva050	Secured Overnight Financing Rate 50 Day MA
3941	SOFRVOL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
3947	SOFR99_YoY	Secured Overnight Financing Rate: 99th Percentile Year over Year
3949	SOFR99_YoY5	Secured Overnight Financing Rate: 99th Percentile 5 Year over 5 Year
3950	SOFR99_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile
3952	SOFR99_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile
3953	SOFR99_Log	Log of Secured Overnight Financing Rate: 99th Percentile
3954	SOFR99_mva200	Secured Overnight Financing Rate: 99th Percentile 200 Day MA
3955	SOFR99_mva050	Secured Overnight Financing Rate: 99th Percentile 50 Day MA
3959	SOFR75_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 75th Percentile
3961	SOFR75_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 75th Percentile
3963	SOFR75_mva200	Secured Overnight Financing Rate: 75th Percentile 200 Day MA
3964	SOFR75_mva050	Secured Overnight Financing Rate: 75th Percentile 50 Day MA
3965	SOFR25_YoY	Secured Overnight Financing Rate: 25th Percentile Year over Year
3968	SOFR25_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 25th Percentile
3970	SOFR25_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 25th Percentile
3971	SOFR25_Log	Log of Secured Overnight Financing Rate: 25th Percentile
3972	SOFR25_mva200	Secured Overnight Financing Rate: 25th Percentile 200 Day MA
3973	SOFR25_mva050	Secured Overnight Financing Rate: 25th Percentile 50 Day MA
3977	SOFR1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 1st Percentile
3979	SOFR1_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 1st Percentile
3980	SOFR1_Log	Log of Secured Overnight Financing Rate: 1st Percentile
3981	SOFR1_mva200	Secured Overnight Financing Rate: 1st Percentile 200 Day MA
3982	SOFR1_mva050	Secured Overnight Financing Rate: 1st Percentile 50 Day MA
3986	OBFR_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate
3988	OBFR_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate
3989	OBFR_Log	Log of Overnight Bank Funding Rate
3990	OBFR_mva200	Overnight Bank Funding Rate 200 Day MA
3991	OBFR_mva050	Overnight Bank Funding Rate 50 Day MA
3992	OBFR99_YoY	Overnight Bank Funding Rate: 99th Percentile Year over Year
3995	OBFR99_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
3996	OBFR99_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Overnight Bank Funding Rate: 99th Percentile
3997	OBFR99_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
3998	OBFR99_Log	Log of Overnight Bank Funding Rate: 99th Percentile
3999	OBFR99_mva200	Overnight Bank Funding Rate: 99th Percentile 200 Day MA
4000	OBFR99_mva050	Overnight Bank Funding Rate: 99th Percentile 50 Day MA
4004	OBFR75_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 75th Percentile
4006	OBFR75_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 75th Percentile
4007	OBFR75_Log	Log of Overnight Bank Funding Rate: 75th Percentile
4008	OBFR75_mva200	Overnight Bank Funding Rate: 75th Percentile 200 Day MA
4009	OBFR75_mva050	Overnight Bank Funding Rate: 75th Percentile 50 Day MA
4013	OBFR25_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 25th Percentile
4015	OBFR25_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
4017	OBFR25_mva200	Overnight Bank Funding Rate: 25th Percentile 200 Day MA
4018	OBFR25_mva050	Overnight Bank Funding Rate: 25th Percentile 50 Day MA
4022	OBFR1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 1st Percentile
4024	OBFR1_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 1st Percentile
4026	OBFR1_mva200	Overnight Bank Funding Rate: 1st Percentile 200 Day MA
4027	OBFR1_mva050	Overnight Bank Funding Rate: 1st Percentile 50 Day MA
4033	RPONTSYD_SmoothDer	Derivative of Smoothed Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4034	RPONTSYD_Log	Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
4037	IOER_YoY	Interest Rate on Excess Reserves Year over Year
4043	IOER_Log	Log of Interest Rate on Excess Reserves
4044	IOER_mva200	Interest Rate on Excess Reserves 200 Day MA
4045	IOER_mva050	Interest Rate on Excess Reserves 50 Day MA
4055	EXCSRESNW_YoY	Excess Reserves of Depository Institutions Year over Year
4061	EXCSRESNW_Log	Log of Excess Reserves of Depository Institutions
4062	EXCSRESNW_mva200	Excess Reserves of Depository Institutions 200 Day MA
4063	EXCSRESNW_mva050	Excess Reserves of Depository Institutions 50 Day MA
4064	ECBASSETS_YoY	Central Bank Assets for Euro Area (11-19 Countries) Year over Year
4070	ECBASSETS_Log	Log of Central Bank Assets for Euro Area (11-19 Countries)
4071	ECBASSETS_mva200	Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
4072	ECBASSETS_mva050	Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
4079	EUNNGDP_Log	Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
4080	EUNNGDP_mva200	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
4081	EUNNGDP_mva050	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
4085	CEU0600000007_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4087	CEU0600000007_SmoothDer	Derivative of Smoothed Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4088	CEU0600000007_Log	Log of Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
4090	CEU0600000007_mva050	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 50 Day MA
4097	CURRENCY_Log	Log of Currency Component of M1 (Seasonally Adjusted)
4098	CURRENCY_mva200	Currency Component of M1 (Seasonally Adjusted) 200 Day MA
4099	CURRENCY_mva050	Currency Component of M1 (Seasonally Adjusted) 50 Day MA
4103	WCURRNS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1
4105	WCURRNS_SmoothDer	Derivative of Smoothed Currency Component of M1
4106	WCURRNS_Log	Log of Currency Component of M1
4107	WCURRNS_mva200	Currency Component of M1 200 Day MA
4108	WCURRNS_mva050	Currency Component of M1 50 Day MA
4120	PRS88003193_YoY5	Nonfinancial Corporations Sector: Unit Profits 5 Year over 5 Year
4123	PRS88003193_SmoothDer	Derivative of Smoothed Nonfinancial Corporations Sector: Unit Profits
4130	PPIACO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index for All Commodities
4132	PPIACO_SmoothDer	Derivative of Smoothed Producer Price Index for All Commodities
4133	PPIACO_Log	Log of Producer Price Index for All Commodities
4134	PPIACO_mva200	Producer Price Index for All Commodities 200 Day MA
4135	PPIACO_mva050	Producer Price Index for All Commodities 50 Day MA
4139	PCUOMFGOMFG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Producer Price Index by Industry: Total Manufacturing Industries
4141	PCUOMFGOMFG_SmoothDer	Derivative of Smoothed Producer Price Index by Industry: Total Manufacturing Industries
4142	PCUOMFGOMFG_Log	Log of Producer Price Index by Industry: Total Manufacturing Industries
4143	PCUOMFGOMFG_mva200	Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
4144	PCUOMFGOMFG_mva050	Producer Price Index by Industry: Total Manufacturing Industries 50 Day MA
4151	POPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4152	POPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
4157	POPTHM_Log	Log of Population (U.S.)
4158	POPTHM_Log	Log of Population (U.S.)
4159	POPTHM_mva200	Population (U.S.) 200 Day MA
4160	POPTHM_mva200	Population (U.S.) 200 Day MA
4161	POPTHM_mva050	Population (U.S.) 50 Day MA
4162	POPTHM_mva050	Population (U.S.) 50 Day MA
4169	POPTHM.1_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4170	POPTHM.1_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4175	POPTHM.1_Log	Log of
4176	POPTHM.1_Log	Log of
4177	POPTHM.1_mva200	200 Day MA
4178	POPTHM.1_mva200	200 Day MA
4179	POPTHM.1_mva050	50 Day MA
4180	POPTHM.1_mva050	50 Day MA
4188	CLF16OV_mva200	Civilian Labor Force Level, SA 200 Day MA
4189	CLF16OV_mva050	Civilian Labor Force Level, SA 50 Day MA
4195	LNU01000000_SmoothDer	Derivative of Smoothed Civilian Labor Force Level, NSA
4197	LNU01000000_mva200	Civilian Labor Force Level, NSA 200 Day MA
4198	LNU01000000_mva050	Civilian Labor Force Level, NSA 50 Day MA
4204	LNU03000000_SmoothDer	Derivative of Smoothed Unemployment Level (NSA)
4208	UNEMPLOY_YoY	Unemployment Level, seasonally adjusted Year over Year
4213	UNEMPLOY_SmoothDer	Derivative of Smoothed Unemployment Level, seasonally adjusted
4222	RSAFS_SmoothDer	Derivative of Smoothed Advance Retail Sales: Retail and Food Services
4224	RSAFS_mva200	Advance Retail Sales: Retail and Food Services 200 Day MA
4229	FRGSHPUSM649NCIS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Cass Freight Index: Shipments
4231	FRGSHPUSM649NCIS_SmoothDer	Derivative of Smoothed Cass Freight Index: Shipments
4232	FRGSHPUSM649NCIS_Log	Log of Cass Freight Index: Shipments
4234	FRGSHPUSM649NCIS_mva050	Cass Freight Index: Shipments 50 Day MA
4238	BOPGTB_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Trade Balance: Goods, Balance of Payments Basis (SA)
4240	BOPGTB_SmoothDer	Derivative of Smoothed Trade Balance: Goods, Balance of Payments Basis (SA)
4241	BOPGTB_Log	Log of Trade Balance: Goods, Balance of Payments Basis (SA)
4245	TERMCBPER24NS_YoY4	Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 4 Year over 4 Year
4249	TERMCBPER24NS_SmoothDer	Derivative of Smoothed Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4250	TERMCBPER24NS_Log	Log of Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
4251	TERMCBPER24NS_mva200	Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 200 Day MA
4252	TERMCBPER24NS_mva050	Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan 50 Day MA
4259	A065RC1A027NBEA_Log	Log of Personal income (NSA)
4260	A065RC1A027NBEA_mva200	Personal income (NSA) 200 Day MA
4261	A065RC1A027NBEA_mva050	Personal income (NSA) 50 Day MA
4268	PI_Log	Log of Personal income (SA)
4269	PI_mva200	Personal income (SA) 200 Day MA
4270	PI_mva050	Personal income (SA) 50 Day MA
4274	PCE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures (SA)
4276	PCE_SmoothDer	Derivative of Smoothed Personal Consumption Expenditures (SA)
4277	PCE_Log	Log of Personal Consumption Expenditures (SA)
4278	PCE_mva200	Personal Consumption Expenditures (SA) 200 Day MA
4279	PCE_mva050	Personal Consumption Expenditures (SA) 50 Day MA
4285	A053RC1Q027SBEA_SmoothDer	Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj)
4286	A053RC1Q027SBEA_Log	Log of National income: Corporate profits before tax (without IVA and CCAdj)
4287	A053RC1Q027SBEA_mva200	National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
4288	A053RC1Q027SBEA_mva050	National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
4294	CPROFIT_SmoothDer	Derivative of Smoothed Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4341	SPY.Volume_mva200	200 Day MA
4448	EES.Volume_Log	Log of
4449	EES.Volume_mva200	200 Day MA
4503	IJR.Volume_mva200	200 Day MA
4550	VGSTX.Volume_YoY	Year over Year
4551	VGSTX.Volume_YoY4	4 Year over 4 Year
4552	VGSTX.Volume_YoY5	5 Year over 5 Year
4553	VGSTX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4554	VGSTX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4555	VGSTX.Volume_SmoothDer	Derivative of Smoothed
4556	VGSTX.Volume_Log	Log of
4557	VGSTX.Volume_mva200	200 Day MA
4558	VGSTX.Volume_mva050	50 Day MA
4604	VFINX.Volume_YoY	Year over Year
4605	VFINX.Volume_YoY4	4 Year over 4 Year
4606	VFINX.Volume_YoY5	5 Year over 5 Year
4607	VFINX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4608	VFINX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4609	VFINX.Volume_SmoothDer	Derivative of Smoothed
4610	VFINX.Volume_Log	Log of
4611	VFINX.Volume_mva200	200 Day MA
4612	VFINX.Volume_mva050	50 Day MA
4663	VOE.Volume_SmoothDer	Derivative of Smoothed
4665	VOE.Volume_mva200	200 Day MA
4666	VOE.Volume_mva050	50 Day MA
4719	VOT.Volume_mva200	200 Day MA
4731	TMFGX.Open_YoY4	4 Year over 4 Year
4732	TMFGX.Open_YoY5	5 Year over 5 Year
4736	TMFGX.Open_Log	Log of
4740	TMFGX.High_YoY4	4 Year over 4 Year
4741	TMFGX.High_YoY5	5 Year over 5 Year
4745	TMFGX.High_Log	Log of
4749	TMFGX.Low_YoY4	4 Year over 4 Year
4750	TMFGX.Low_YoY5	5 Year over 5 Year
4754	TMFGX.Low_Log	Log of
4758	TMFGX.Close_YoY4	4 Year over 4 Year
4759	TMFGX.Close_YoY5	5 Year over 5 Year
4763	TMFGX.Close_Log	Log of
4766	TMFGX.Volume_YoY	Year over Year
4767	TMFGX.Volume_YoY4	4 Year over 4 Year
4768	TMFGX.Volume_YoY5	5 Year over 5 Year
4769	TMFGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4770	TMFGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4771	TMFGX.Volume_SmoothDer	Derivative of Smoothed
4772	TMFGX.Volume_Log	Log of
4773	TMFGX.Volume_mva200	200 Day MA
4774	TMFGX.Volume_mva050	50 Day MA
4776	TMFGX.Adjusted_YoY4	4 Year over 4 Year
4777	TMFGX.Adjusted_YoY5	5 Year over 5 Year
4781	TMFGX.Adjusted_Log	Log of
4874	ONEQ.Volume_YoY	Year over Year
4875	ONEQ.Volume_YoY4	4 Year over 4 Year
4881	ONEQ.Volume_mva200	200 Day MA
4882	ONEQ.Volume_mva050	50 Day MA
4928	FSMAX.Volume_YoY	Year over Year
4929	FSMAX.Volume_YoY4	4 Year over 4 Year
4930	FSMAX.Volume_YoY5	5 Year over 5 Year
4931	FSMAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4932	FSMAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4933	FSMAX.Volume_SmoothDer	Derivative of Smoothed
4934	FSMAX.Volume_Log	Log of
4935	FSMAX.Volume_mva200	200 Day MA
4936	FSMAX.Volume_mva050	50 Day MA
4982	FXNAX.Volume_YoY	Year over Year
4983	FXNAX.Volume_YoY4	4 Year over 4 Year
4984	FXNAX.Volume_YoY5	5 Year over 5 Year
4985	FXNAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4986	FXNAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4987	FXNAX.Volume_SmoothDer	Derivative of Smoothed
4988	FXNAX.Volume_Log	Log of
4989	FXNAX.Volume_mva200	200 Day MA
4990	FXNAX.Volume_mva050	50 Day MA
5036	HAINX.Volume_YoY	Year over Year
5037	HAINX.Volume_YoY4	4 Year over 4 Year
5038	HAINX.Volume_YoY5	5 Year over 5 Year
5039	HAINX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5040	HAINX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5041	HAINX.Volume_SmoothDer	Derivative of Smoothed
5042	HAINX.Volume_Log	Log of
5043	HAINX.Volume_mva200	200 Day MA
5044	HAINX.Volume_mva050	50 Day MA
5090	HNACX.Volume_YoY	Year over Year
5091	HNACX.Volume_YoY4	4 Year over 4 Year
5092	HNACX.Volume_YoY5	5 Year over 5 Year
5093	HNACX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5094	HNACX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5095	HNACX.Volume_SmoothDer	Derivative of Smoothed
5096	HNACX.Volume_Log	Log of
5097	HNACX.Volume_mva200	200 Day MA
5098	HNACX.Volume_mva050	50 Day MA
5151	VEU.Volume_mva200	200 Day MA
5167	VEIRX.Open_SmoothDer	Derivative of Smoothed
5176	VEIRX.High_SmoothDer	Derivative of Smoothed
5185	VEIRX.Low_SmoothDer	Derivative of Smoothed
5194	VEIRX.Close_SmoothDer	Derivative of Smoothed
5198	VEIRX.Volume_YoY	Year over Year
5199	VEIRX.Volume_YoY4	4 Year over 4 Year
5200	VEIRX.Volume_YoY5	5 Year over 5 Year
5201	VEIRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5202	VEIRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5203	VEIRX.Volume_SmoothDer	Derivative of Smoothed
5204	VEIRX.Volume_Log	Log of
5205	VEIRX.Volume_mva200	200 Day MA
5206	VEIRX.Volume_mva050	50 Day MA
5219	BIL.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5221	BIL.Open_SmoothDer	Derivative of Smoothed
5224	BIL.Open_mva050	50 Day MA
5228	BIL.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5230	BIL.High_SmoothDer	Derivative of Smoothed
5233	BIL.High_mva050	50 Day MA
5237	BIL.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5239	BIL.Low_SmoothDer	Derivative of Smoothed
5246	BIL.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5248	BIL.Close_SmoothDer	Derivative of Smoothed
5251	BIL.Close_mva050	50 Day MA
5255	BIL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5257	BIL.Volume_SmoothDer	Derivative of Smoothed
5259	BIL.Volume_mva200	200 Day MA
5264	BIL.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5265	BIL.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5266	BIL.Adjusted_SmoothDer	Derivative of Smoothed
5267	BIL.Adjusted_Log	Log of
5269	BIL.Adjusted_mva050	50 Day MA
5312	IVOO.Volume_Log	Log of
5362	VO.Volume_YoY5	5 Year over 5 Year
5366	VO.Volume_Log	Log of
5367	VO.Volume_mva200	200 Day MA
5417	CZA.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5420	CZA.Volume_Log	Log of
5470	VYM.Volume_YoY5	5 Year over 5 Year
5475	VYM.Volume_mva200	200 Day MA
5576	SLY.Volume_YoY	Year over Year
5582	SLY.Volume_Log	Log of
5583	SLY.Volume_mva200	200 Day MA
5637	QQQ.Volume_mva200	200 Day MA
5687	HYMB.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5688	HYMB.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5689	HYMB.Volume_SmoothDer	Derivative of Smoothed
5690	HYMB.Volume_Log	Log of
5691	HYMB.Volume_mva200	200 Day MA
5692	HYMB.Volume_mva050	50 Day MA
5707	GOLD.Open_SmoothDer	Derivative of Smoothed
5708	GOLD.Open_Log	Log of
5709	GOLD.Open_mva200	200 Day MA
5716	GOLD.High_SmoothDer	Derivative of Smoothed
5718	GOLD.High_mva200	200 Day MA
5725	GOLD.Low_SmoothDer	Derivative of Smoothed
5727	GOLD.Low_mva200	200 Day MA
5734	GOLD.Close_SmoothDer	Derivative of Smoothed
5736	GOLD.Close_mva200	200 Day MA
5744	GOLD.Volume_Log	Log of
5752	GOLD.Adjusted_SmoothDer	Derivative of Smoothed
5754	GOLD.Adjusted_mva200	200 Day MA
5759	BKR.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5761	BKR.Open_SmoothDer	Derivative of Smoothed
5762	BKR.Open_Log	Log of
5763	BKR.Open_mva200	200 Day MA
5768	BKR.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5770	BKR.High_SmoothDer	Derivative of Smoothed
5772	BKR.High_mva200	200 Day MA
5777	BKR.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5779	BKR.Low_SmoothDer	Derivative of Smoothed
5781	BKR.Low_mva200	200 Day MA
5786	BKR.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5788	BKR.Close_SmoothDer	Derivative of Smoothed
5790	BKR.Close_mva200	200 Day MA
5798	BKR.Volume_Log	Log of
5799	BKR.Volume_mva200	200 Day MA
5804	BKR.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5806	BKR.Adjusted_SmoothDer	Derivative of Smoothed
5808	BKR.Adjusted_mva200	200 Day MA
5813	SLB.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5815	SLB.Open_SmoothDer	Derivative of Smoothed
5817	SLB.Open_mva200	200 Day MA
5818	SLB.Open_mva050	50 Day MA
5822	SLB.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5824	SLB.High_SmoothDer	Derivative of Smoothed
5826	SLB.High_mva200	200 Day MA
5827	SLB.High_mva050	50 Day MA
5831	SLB.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5833	SLB.Low_SmoothDer	Derivative of Smoothed
5835	SLB.Low_mva200	200 Day MA
5840	SLB.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5842	SLB.Close_SmoothDer	Derivative of Smoothed
5844	SLB.Close_mva200	200 Day MA
5853	SLB.Volume_mva200	200 Day MA
5858	SLB.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5860	SLB.Adjusted_SmoothDer	Derivative of Smoothed
5862	SLB.Adjusted_mva200	200 Day MA
5867	HAL.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5869	HAL.Open_SmoothDer	Derivative of Smoothed
5870	HAL.Open_Log	Log of
5871	HAL.Open_mva200	200 Day MA
5876	HAL.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5878	HAL.High_SmoothDer	Derivative of Smoothed
5880	HAL.High_mva200	200 Day MA
5885	HAL.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5887	HAL.Low_SmoothDer	Derivative of Smoothed
5889	HAL.Low_mva200	200 Day MA
5894	HAL.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5896	HAL.Close_SmoothDer	Derivative of Smoothed
5898	HAL.Close_mva200	200 Day MA
5906	HAL.Volume_Log	Log of
5907	HAL.Volume_mva200	200 Day MA
5912	HAL.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5914	HAL.Adjusted_SmoothDer	Derivative of Smoothed
5916	HAL.Adjusted_mva200	200 Day MA
5921	IP.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5923	IP.Open_SmoothDer	Derivative of Smoothed
5924	IP.Open_Log	Log of
5930	IP.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5932	IP.High_SmoothDer	Derivative of Smoothed
5939	IP.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5941	IP.Low_SmoothDer	Derivative of Smoothed
5948	IP.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5950	IP.Close_SmoothDer	Derivative of Smoothed
5961	IP.Volume_mva200	200 Day MA
5966	IP.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5968	IP.Adjusted_SmoothDer	Derivative of Smoothed
5975	PKG.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5977	PKG.Open_SmoothDer	Derivative of Smoothed
5979	PKG.Open_mva200	200 Day MA
5984	PKG.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5986	PKG.High_SmoothDer	Derivative of Smoothed
5988	PKG.High_mva200	200 Day MA
5993	PKG.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5995	PKG.Low_SmoothDer	Derivative of Smoothed
5997	PKG.Low_mva200	200 Day MA
6002	PKG.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6004	PKG.Close_SmoothDer	Derivative of Smoothed
6006	PKG.Close_mva200	200 Day MA
6020	PKG.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6022	PKG.Adjusted_SmoothDer	Derivative of Smoothed
6024	PKG.Adjusted_mva200	200 Day MA
6067	UPS.Volume_SmoothDer	Derivative of Smoothed
6069	UPS.Volume_mva200	200 Day MA
6085	FDX.Open_SmoothDer	Derivative of Smoothed
6094	FDX.High_SmoothDer	Derivative of Smoothed
6103	FDX.Low_SmoothDer	Derivative of Smoothed
6112	FDX.Close_SmoothDer	Derivative of Smoothed
6119	FDX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6120	FDX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
6130	FDX.Adjusted_SmoothDer	Derivative of Smoothed
6137	T.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6139	T.Open_SmoothDer	Derivative of Smoothed
6140	T.Open_Log	Log of
6142	T.Open_mva050	50 Day MA
6146	T.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6148	T.High_SmoothDer	Derivative of Smoothed
6155	T.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6157	T.Low_SmoothDer	Derivative of Smoothed
6164	T.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6166	T.Close_SmoothDer	Derivative of Smoothed
6182	T.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6184	T.Adjusted_SmoothDer	Derivative of Smoothed
6193	VZ.Open_SmoothDer	Derivative of Smoothed
6202	VZ.High_SmoothDer	Derivative of Smoothed
6211	VZ.Low_SmoothDer	Derivative of Smoothed
6220	VZ.Close_SmoothDer	Derivative of Smoothed
6238	VZ.Adjusted_SmoothDer	Derivative of Smoothed
6247	ISMMANPMI_SmoothDer	Derivative of Smoothed Institute of Supply Managment PMI Composite Index
6256	MULTPLSP500PERATIOMONTH_SmoothDer	Derivative of Smoothed S&P 500 TTM P/E
6266	MULTPLSP500SALESQUARTER_Log	Log of S&P 500 TTM Sales (Not Inflation Adjusted)
6267	MULTPLSP500SALESQUARTER_mva200	S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
6268	MULTPLSP500SALESQUARTER_mva050	S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
6269	MULTPLSP500DIVYIELDMONTH_YoY	S&P 500 Dividend Yield by Month Year over Year
6270	MULTPLSP500DIVYIELDMONTH_YoY4	S&P 500 Dividend Yield by Month 4 Year over 4 Year
6271	MULTPLSP500DIVYIELDMONTH_YoY5	S&P 500 Dividend Yield by Month 5 Year over 5 Year
6272	MULTPLSP500DIVYIELDMONTH_Smooth	Savitsky-Golay Smoothed (p=3, n=365) S&P 500 Dividend Yield by Month
6274	MULTPLSP500DIVYIELDMONTH_SmoothDer	Derivative of Smoothed S&P 500 Dividend Yield by Month
6275	MULTPLSP500DIVYIELDMONTH_Log	Log of S&P 500 Dividend Yield by Month
6276	MULTPLSP500DIVYIELDMONTH_mva200	S&P 500 Dividend Yield by Month 200 Day MA
6277	MULTPLSP500DIVYIELDMONTH_mva050	S&P 500 Dividend Yield by Month 50 Day MA
6278	MULTPLSP500DIVMONTH_YoY	S&P 500 Dividend by Month (Inflation Adjusted) Year over Year
6290	CHRISCMEHG1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6292	CHRISCMEHG1_SmoothDer	Derivative of Smoothed Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6293	CHRISCMEHG1_Log	Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
6295	CHRISCMEHG1_mva050	Copper Futures, Continuous Contract #1 (HG1) (Front Month) 50 Day MA
6296	WWDIWLDISAIRGOODMTK1_YoY	Air transport, freight Year over Year
6302	WWDIWLDISAIRGOODMTK1_Log	Log of Air transport, freight
6303	WWDIWLDISAIRGOODMTK1_mva200	Air transport, freight 200 Day MA
6304	WWDIWLDISAIRGOODMTK1_mva050	Air transport, freight 50 Day MA
6312	LBMAGOLD.USD_AM_mva200	200 Day MA
6321	LBMAGOLD.USD_PM_mva200	200 Day MA
6326	LBMAGOLD.GBP_AM_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6328	LBMAGOLD.GBP_AM_SmoothDer	Derivative of Smoothed
6330	LBMAGOLD.GBP_AM_mva200	200 Day MA
6335	LBMAGOLD.GBP_PM_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6337	LBMAGOLD.GBP_PM_SmoothDer	Derivative of Smoothed
6339	LBMAGOLD.GBP_PM_mva200	200 Day MA
6346	LBMAGOLD.EURO_AM_SmoothDer	Derivative of Smoothed
6348	LBMAGOLD.EURO_AM_mva200	200 Day MA
6355	LBMAGOLD.EURO_PM_SmoothDer	Derivative of Smoothed
6357	LBMAGOLD.EURO_PM_mva200	200 Day MA
6359	PETA103600001M_YoY	U.S. Total Gasoline Retail Sales by Refiners, Monthly Year over Year
6366	PETA103600001M_mva200	U.S. Total Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6368	PETA123600001M_YoY	U.S. Regular Gasoline Retail Sales by Refiners, Monthly Year over Year
6374	PETA123600001M_Log	Log of U.S. Regular Gasoline Retail Sales by Refiners, Monthly
6375	PETA123600001M_mva200	U.S. Regular Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6376	PETA123600001M_mva050	U.S. Regular Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6377	PETA143B00001M_YoY	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
6378	PETA143B00001M_YoY4	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
6379	PETA143B00001M_YoY5	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
6383	PETA143B00001M_Log	Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
6384	PETA143B00001M_mva200	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
6385	PETA143B00001M_mva050	U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
6401	TOTALOGNRPUSM_Log	Log of Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
6402	TOTALOGNRPUSM_mva200	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 200 Day MA
6403	TOTALOGNRPUSM_mva050	Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 50 Day MA
6410	TOTALPANRPUSM_Log	Log of Crude Oil Rotary Rigs in Operation, Monthly
6411	TOTALPANRPUSM_mva200	Crude Oil Rotary Rigs in Operation, Monthly 200 Day MA
6412	TOTALPANRPUSM_mva050	Crude Oil Rotary Rigs in Operation, Monthly 50 Day MA
6414	TOTALNGNRPUSM_YoY4	Natural Gas Rotary Rigs in Operation, Monthly 4 Year over 4 Year
6418	TOTALNGNRPUSM_SmoothDer	Derivative of Smoothed Natural Gas Rotary Rigs in Operation, Monthly
6419	TOTALNGNRPUSM_Log	Log of Natural Gas Rotary Rigs in Operation, Monthly
6420	TOTALNGNRPUSM_mva200	Natural Gas Rotary Rigs in Operation, Monthly 200 Day MA
6421	TOTALNGNRPUSM_mva050	Natural Gas Rotary Rigs in Operation, Monthly 50 Day MA
6428	BKRTotal_Log	Log of Total Rig Count
6429	BKRTotal_mva200	Total Rig Count 200 Day MA
6430	BKRTotal_mva050	Total Rig Count 50 Day MA
6434	BKRGas_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Gas Rig Count
6436	BKRGas_SmoothDer	Derivative of Smoothed Gas Rig Count
6437	BKRGas_Log	Log of Gas Rig Count
6438	BKRGas_mva200	Gas Rig Count 200 Day MA
6439	BKRGas_mva050	Gas Rig Count 50 Day MA
6446	BKROil_Log	Log of Oil Rig Count
6447	BKROil_mva200	Oil Rig Count 200 Day MA
6448	BKROil_mva050	Oil Rig Count 50 Day MA
6449	FARMINCOME_YoY	Net Farm Income Year over Year
6455	FARMINCOME_Log	Log of Net Farm Income
6456	FARMINCOME_mva200	Net Farm Income 200 Day MA
6457	FARMINCOME_mva050	Net Farm Income 50 Day MA
6464	OPEARNINGSPERSHARE_Log	Log of Operating Earnings per Share
6465	OPEARNINGSPERSHARE_mva200	Operating Earnings per Share 200 Day MA
6466	OPEARNINGSPERSHARE_mva050	Operating Earnings per Share 50 Day MA
6473	AREARNINGSPERSHARE_Log	Log of As-Reported Earnings per Share
6474	AREARNINGSPERSHARE_mva200	As-Reported Earnings per Share 200 Day MA
6475	AREARNINGSPERSHARE_mva050	As-Reported Earnings per Share 50 Day MA
6476	CASHDIVIDENDSPERSHR_YoY	Cash Dividends per Share Year over Year
6482	CASHDIVIDENDSPERSHR_Log	Log of Cash Dividends per Share
6483	CASHDIVIDENDSPERSHR_mva200	Cash Dividends per Share 200 Day MA
6484	CASHDIVIDENDSPERSHR_mva050	Cash Dividends per Share 50 Day MA
6491	SALESPERSHR_Log	Log of Sales per Share
6492	SALESPERSHR_mva200	Sales per Share 200 Day MA
6493	SALESPERSHR_mva050	Sales per Share 50 Day MA
6500	BOOKVALPERSHR_Log	Log of Book value per Share
6501	BOOKVALPERSHR_mva200	Book value per Share 200 Day MA
6502	BOOKVALPERSHR_mva050	Book value per Share 50 Day MA
6509	CAPEXPERSHR_Log	Log of Cap ex per Share
6510	CAPEXPERSHR_mva200	Cap ex per Share 200 Day MA
6511	CAPEXPERSHR_mva050	Cap ex per Share 50 Day MA
6518	PRICE_Log	Log of Price
6519	PRICE_mva200	Price 200 Day MA
6520	PRICE_mva050	Price 50 Day MA
6527	OPEARNINGSTTM_Log	Log of TTM Operating Earnings
6528	OPEARNINGSTTM_mva200	TTM Operating Earnings 200 Day MA
6529	OPEARNINGSTTM_mva050	TTM Operating Earnings 50 Day MA
6536	AREARNINGSTTM_Log	Log of TTM Reported Earnings
6537	AREARNINGSTTM_mva200	TTM Reported Earnings 200 Day MA
6538	AREARNINGSTTM_mva050	TTM Reported Earnings 50 Day MA
6545	FINRAMarginDebt_Log	Log of Margin Debt
6547	FINRAMarginDebt_mva050	Margin Debt 50 Day MA
6553	FINRAFreeCreditMargin_SmoothDer	Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
6554	FINRAFreeCreditMargin_Log	Log of Free Credit Balances in Customers’ Securities Margin Accounts
6556	FINRAFreeCreditMargin_mva050	Free Credit Balances in Customers’ Securities Margin Accounts 50 Day MA
6557	OCCEquityVolume_YoY	Equity Options Volume Year over Year
6563	OCCEquityVolume_Log	Log of Equity Options Volume
6564	OCCEquityVolume_mva200	Equity Options Volume 200 Day MA
6565	OCCEquityVolume_mva050	Equity Options Volume 50 Day MA
6566	OCCNonEquityVolume_YoY	Non-Equity Options Volume Year over Year
6572	OCCNonEquityVolume_Log	Log of Non-Equity Options Volume
6573	OCCNonEquityVolume_mva200	Non-Equity Options Volume 200 Day MA
6574	OCCNonEquityVolume_mva050	Non-Equity Options Volume 50 Day MA
6580	RSALESAGG_SmoothDer	Derivative of Smoothed Real Retail and Food Services Sales (RRSFS and RSALES)
6582	RSALESAGG_mva200	Real Retail and Food Services Sales (RRSFS and RSALES) 200 Day MA
6590	BUSLOANS.minus.BUSLOANSNSA_Log	Log of Business Loans (Montlhy) SA - NSA
6599	BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log	Log of Business Loans (Montlhy) SA - NSA divided by GDP
6602	BUSLOANS.by.GDP_YoY	Business Loans Normalized by GDP Year over Year
6604	BUSLOANS.by.GDP_YoY5	Business Loans Normalized by GDP 5 Year over 5 Year
6605	BUSLOANS.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6607	BUSLOANS.by.GDP_SmoothDer	Derivative of Smoothed Business Loans Normalized by GDP
6608	BUSLOANS.by.GDP_Log	Log of Business Loans Normalized by GDP
6609	BUSLOANS.by.GDP_mva200	Business Loans Normalized by GDP 200 Day MA
6610	BUSLOANS.by.GDP_mva050	Business Loans Normalized by GDP 50 Day MA
6614	BUSLOANS.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
6616	BUSLOANS.INTEREST_SmoothDer	Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
6618	BUSLOANS.INTEREST_mva200	Business Loans (Monthly, SA) Adjusted Interest Burdens 200 Day MA
6619	BUSLOANS.INTEREST_mva050	Business Loans (Monthly, SA) Adjusted Interest Burdens 50 Day MA
6623	BUSLOANS.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6625	BUSLOANS.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6627	BUSLOANS.INTEREST.by.GDP_mva200	Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 200 Day MA
6628	BUSLOANS.INTEREST.by.GDP_mva050	Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 50 Day MA
6629	BUSLOANSNSA.by.GDP_YoY	Business Loans Normalized by GDP Year over Year
6631	BUSLOANSNSA.by.GDP_YoY5	Business Loans Normalized by GDP 5 Year over 5 Year
6632	BUSLOANSNSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6634	BUSLOANSNSA.by.GDP_SmoothDer	Derivative of Smoothed Business Loans Normalized by GDP
6635	BUSLOANSNSA.by.GDP_Log	Log of Business Loans Normalized by GDP
6636	BUSLOANSNSA.by.GDP_mva200	Business Loans Normalized by GDP 200 Day MA
6637	BUSLOANSNSA.by.GDP_mva050	Business Loans Normalized by GDP 50 Day MA
6638	TOTCI.by.GDP_YoY	Business Loans (Weekly, SA) Normalized by GDP Year over Year
6641	TOTCI.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, SA) Normalized by GDP
6643	TOTCI.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
6644	TOTCI.by.GDP_Log	Log of Business Loans (Weekly, SA) Normalized by GDP
6645	TOTCI.by.GDP_mva200	Business Loans (Weekly, SA) Normalized by GDP 200 Day MA
6646	TOTCI.by.GDP_mva050	Business Loans (Weekly, SA) Normalized by GDP 50 Day MA
6647	TOTCINSA.by.GDP_YoY	Business Loans (Weekly, NSA) Normalized by GDP Year over Year
6650	TOTCINSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Normalized by GDP
6652	TOTCINSA.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
6653	TOTCINSA.by.GDP_Log	Log of Business Loans (Weekly, NSA) Normalized by GDP
6654	TOTCINSA.by.GDP_mva200	Business Loans (Weekly, NSA) Normalized by GDP 200 Day MA
6655	TOTCINSA.by.GDP_mva050	Business Loans (Weekly, NSA) Normalized by GDP 50 Day MA
6659	TOTCINSA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6661	TOTCINSA.INTEREST_SmoothDer	Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
6663	TOTCINSA.INTEREST_mva200	Business Loans (Weekly, NSA) Adjusted Interest Burdens 200 Day MA
6664	TOTCINSA.INTEREST_mva050	Business Loans (Weekly, NSA) Adjusted Interest Burdens 50 Day MA
6668	TOTCINSA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6670	TOTCINSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6672	TOTCINSA.INTEREST.by.GDP_mva200	Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 200 Day MA
6673	TOTCINSA.INTEREST.by.GDP_mva050	Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 50 Day MA
6674	W875RX1.by.GDP_YoY	Real Personal Income Normalized by GDP Year over Year
6676	W875RX1.by.GDP_YoY5	Real Personal Income Normalized by GDP 5 Year over 5 Year
6679	W875RX1.by.GDP_SmoothDer	Derivative of Smoothed Real Personal Income Normalized by GDP
6680	W875RX1.by.GDP_Log	Log of Real Personal Income Normalized by GDP
6683	A065RC1A027NBEA.by.GDP_YoY	Personal Income (NSA) Normalized by GDP Year over Year
6688	A065RC1A027NBEA.by.GDP_SmoothDer	Derivative of Smoothed Personal Income (NSA) Normalized by GDP
6694	PI.by.GDP_YoY5	Personal Income (SA) Normalized by GDP 5 Year over 5 Year
6698	PI.by.GDP_Log	Log of Personal Income (SA) Normalized by GDP
6700	PI.by.GDP_mva050	Personal Income (SA) Normalized by GDP 50 Day MA
6706	A053RC1Q027SBEA.by.GDP_SmoothDer	Derivative of Smoothed National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6707	A053RC1Q027SBEA.by.GDP_Log	Log of National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP
6709	A053RC1Q027SBEA.by.GDP_mva050	National income: Corporate profits before tax (without IVA and CCAdj) Normalized by GDP 50 Day MA
6715	CPROFIT.by.GDP_SmoothDer	Derivative of Smoothed National income: Corporate profits before tax (with IVA and CCAdj) Normalized by GDP
6722	CONSUMERNSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
6724	CONSUMERNSA.by.GDP_SmoothDer	Derivative of Smoothed Consumer Loans Not Seasonally Adjusted divided by GDP
6725	CONSUMERNSA.by.GDP_Log	Log of Consumer Loans Not Seasonally Adjusted divided by GDP
6726	CONSUMERNSA.by.GDP_mva200	Consumer Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6727	CONSUMERNSA.by.GDP_mva050	Consumer Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6728	RREACBM027NBOG.by.GDP_YoY	Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
6731	RREACBM027NBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
6733	RREACBM027NBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
6734	RREACBM027NBOG.by.GDP_Log	Log of Residental Real Estate Loans (Monthly, NSA) divided by GDP
6736	RREACBM027NBOG.by.GDP_mva050	Residental Real Estate Loans (Monthly, NSA) divided by GDP 50 Day MA
6737	RREACBM027SBOG.by.GDP_YoY	Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
6738	RREACBM027SBOG.by.GDP_YoY4	Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
6739	RREACBM027SBOG.by.GDP_YoY5	Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
6740	RREACBM027SBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
6742	RREACBM027SBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
6743	RREACBM027SBOG.by.GDP_Log	Log of Residental Real Estate Loans (Monthly, SA) divided by GDP
6744	RREACBM027SBOG.by.GDP_mva200	Residental Real Estate Loans (Monthly, SA) divided by GDP 200 Day MA
6745	RREACBM027SBOG.by.GDP_mva050	Residental Real Estate Loans (Monthly, SA) divided by GDP 50 Day MA
6746	RREACBW027SBOG.by.GDP_YoY	Residental Real Estate Loans (Weekly, SA) divided by GDP Year over Year
6749	RREACBW027SBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
6751	RREACBW027SBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
6752	RREACBW027SBOG.by.GDP_Log	Log of Residental Real Estate Loans (Weekly, SA) divided by GDP
6753	RREACBW027SBOG.by.GDP_mva200	Residental Real Estate Loans (Weekly, SA) divided by GDP 200 Day MA
6754	RREACBW027SBOG.by.GDP_mva050	Residental Real Estate Loans (Weekly, SA) divided by GDP 50 Day MA
6755	RREACBW027NBOG.by.GDP_YoY	Residental Real Estate Loans (Weekly, NSA) divided by GDP Year over Year
6757	RREACBW027NBOG.by.GDP_YoY5	Residental Real Estate Loans (Weekly, NSA) divided by GDP 5 Year over 5 Year
6758	RREACBW027NBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
6760	RREACBW027NBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
6761	RREACBW027NBOG.by.GDP_Log	Log of Residental Real Estate Loans (Weekly, NSA) divided by GDP
6763	RREACBW027NBOG.by.GDP_mva050	Residental Real Estate Loans (Weekly, NSA) divided by GDP 50 Day MA
6779	DGORDER.by.GDP_Log	Log of Durable Goods (Monthly, NSA) divided by GDP
6780	DGORDER.by.GDP_mva200	Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6781	DGORDER.by.GDP_mva050	Durable Goods (Monthly, NSA) divided by GDP 50 Day MA
6784	ASHMA.by.GDP_YoY5	Home Mortgages (Quarterly, NSA) divided by GDP 5 Year over 5 Year
6787	ASHMA.by.GDP_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
6788	ASHMA.by.GDP_Log	Log of Home Mortgages (Quarterly, NSA) divided by GDP
6790	ASHMA.by.GDP_mva050	Home Mortgages (Quarterly, NSA) divided by GDP 50 Day MA
6791	ASHMA.INTEREST_YoY	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Year over Year
6792	ASHMA.INTEREST_YoY4	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6793	ASHMA.INTEREST_YoY5	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6794	ASHMA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6795	ASHMA.INTEREST_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6796	ASHMA.INTEREST_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6797	ASHMA.INTEREST_Log	Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6798	ASHMA.INTEREST_mva200	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6799	ASHMA.INTEREST_mva050	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6800	ASHMA.INTEREST.by.GDP_YoY	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP Year over Year
6801	ASHMA.INTEREST.by.GDP_YoY4	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 4 Year over 4 Year
6802	ASHMA.INTEREST.by.GDP_YoY5	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 5 Year over 5 Year
6803	ASHMA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6804	ASHMA.INTEREST.by.GDP_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6805	ASHMA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6806	ASHMA.INTEREST.by.GDP_Log	Log of Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP
6807	ASHMA.INTEREST.by.GDP_mva200	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 200 Day MA
6808	ASHMA.INTEREST.by.GDP_mva050	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Divided by GDP 50 Day MA
6810	CONSUMERNSA.INTEREST_YoY4	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 4 Year over 4 Year
6811	CONSUMERNSA.INTEREST_YoY5	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 5 Year over 5 Year
6814	CONSUMERNSA.INTEREST_SmoothDer	Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6815	CONSUMERNSA.INTEREST_Log	Log of Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6816	CONSUMERNSA.INTEREST_mva200	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
6817	CONSUMERNSA.INTEREST_mva050	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 50 Day MA
6819	CONSUMERNSA.INTEREST.by.GDP_YoY4	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 4 Year over 4 Year
6820	CONSUMERNSA.INTEREST.by.GDP_YoY5	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 5 Year over 5 Year
6823	CONSUMERNSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6824	CONSUMERNSA.INTEREST.by.GDP_Log	Log of Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6825	CONSUMERNSA.INTEREST.by.GDP_mva200	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 200 Day MA
6826	CONSUMERNSA.INTEREST.by.GDP_mva050	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 50 Day MA
6830	TOTLNNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6833	TOTLNNSA_Log	Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6834	TOTLNNSA_mva200	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
6835	TOTLNNSA_mva050	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
6836	TOTLNNSA.by.GDP_YoY	Total Loans Not Seasonally Adjusted divided by GDP Year over Year
6839	TOTLNNSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
6841	TOTLNNSA.by.GDP_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
6842	TOTLNNSA.by.GDP_Log	Log of Total Loans Not Seasonally Adjusted divided by GDP
6843	TOTLNNSA.by.GDP_mva200	Total Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6844	TOTLNNSA.by.GDP_mva050	Total Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6848	TOTLNNSA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
6850	TOTLNNSA.INTEREST_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
6852	TOTLNNSA.INTEREST_mva200	Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
6853	TOTLNNSA.INTEREST_mva050	Total Loans Not Seasonally Adjusted Interest Burdens 50 Day MA
6857	TOTLNNSA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6859	TOTLNNSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6861	TOTLNNSA.INTEREST.by.GDP_mva200	Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 200 Day MA
6862	TOTLNNSA.INTEREST.by.GDP_mva050	Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 50 Day MA
6872	EXCSRESNW.by.GDP_YoY	Excess Reserves of Depository Institutions Divided by GDP Year over Year
6877	EXCSRESNW.by.GDP_SmoothDer	Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
6884	WLRRAL.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6887	WLRRAL.by.GDP_Log	Log of Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6888	WLRRAL.by.GDP_mva200	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 200 Day MA
6889	WLRRAL.by.GDP_mva050	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 50 Day MA
6893	SOFR99.minus.SOFR1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6895	SOFR99.minus.SOFR1_SmoothDer	Derivative of Smoothed Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6897	SOFR99.minus.SOFR1_mva200	Secured Overnight Financing Rate: 99th Percentile - 1st Percentile 200 Day MA
6902	EXPCH.minus.IMPCH_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6904	EXPCH.minus.IMPCH_SmoothDer	Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6905	EXPCH.minus.IMPCH_Log	Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6907	EXPCH.minus.IMPCH_mva050	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 50 Day MA
6914	EXPMX.minus.IMPMX_Log	Log of
6918	SRPSABSNNCB.by.GDP_YoY4	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6919	SRPSABSNNCB.by.GDP_YoY5	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 5 Year over 5 Year
6923	SRPSABSNNCB.by.GDP_Log	Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6924	SRPSABSNNCB.by.GDP_mva200	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 200 Day MA
6925	SRPSABSNNCB.by.GDP_mva050	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 50 Day MA
6932	ASTLL.by.GDP_Log	Log of All sectors; total loans; liability, Level (NSA) Divided by GDP
6933	ASTLL.by.GDP_mva200	All sectors; total loans; liability, Level (NSA) Divided by GDP 200 Day MA
6934	ASTLL.by.GDP_mva050	All sectors; total loans; liability, Level (NSA) Divided by GDP 50 Day MA
6935	ASFMA.by.GDP_YoY	All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
6940	ASFMA.by.GDP_SmoothDer	Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6944	ASFMA.by.ASTLL_YoY	All sectors; total loans Divided by farm mortgages Year over Year
6949	ASFMA.by.ASTLL_SmoothDer	Derivative of Smoothed All sectors; total loans Divided by farm mortgages
6953	ASFMA.INTEREST_YoY	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens Year over Year
6954	ASFMA.INTEREST_YoY4	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 4 Year over 4 Year
6955	ASFMA.INTEREST_YoY5	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 5 Year over 5 Year
6956	ASFMA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6957	ASFMA.INTEREST_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6958	ASFMA.INTEREST_SmoothDer	Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6959	ASFMA.INTEREST_Log	Log of Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6960	ASFMA.INTEREST_mva200	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6961	ASFMA.INTEREST_mva050	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6962	ASFMA.INTEREST.by.GDP_YoY	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP Year over Year
6963	ASFMA.INTEREST.by.GDP_YoY4	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 4 Year over 4 Year
6964	ASFMA.INTEREST.by.GDP_YoY5	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 5 Year over 5 Year
6965	ASFMA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6966	ASFMA.INTEREST.by.GDP_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6967	ASFMA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6968	ASFMA.INTEREST.by.GDP_Log	Log of Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6969	ASFMA.INTEREST.by.GDP_mva200	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 200 Day MA
6970	ASFMA.INTEREST.by.GDP_mva050	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
6971	FARMINCOME.by.GDP_YoY	Farm Income (Annual, NSA) Divided by GDP Year over Year
6976	FARMINCOME.by.GDP_SmoothDer	Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
6981	BOGMBASE.by.GDP_YoY4	BOGMBASE Divided by GDP 4 Year over 4 Year
6985	BOGMBASE.by.GDP_SmoothDer	Derivative of Smoothed BOGMBASE Divided by GDP
6990	WALCL.by.GDP_YoY4	All Federal Reserve Banks: Total Assets Divided by GDP 4 Year over 4 Year
6991	WALCL.by.GDP_YoY5	All Federal Reserve Banks: Total Assets Divided by GDP 5 Year over 5 Year
6996	WALCL.by.GDP_mva200	All Federal Reserve Banks: Total Assets Divided by GDP 200 Day MA
6998	ECBASSETS.by.EUNNGDP_YoY	Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
7003	ECBASSETS.by.EUNNGDP_SmoothDer	Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
7012	DGS30TO10_SmoothDer	Derivative of Smoothed Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7013	DGS30TO10_Log	Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
7022	DGS10TO1_Log	Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
7030	DGS10TO2_SmoothDer	Derivative of Smoothed Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7031	DGS10TO2_Log	Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
7037	DGS10TOTB3MS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7039	DGS10TOTB3MS_SmoothDer	Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7040	DGS10TOTB3MS_Log	Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
7041	DGS10TOTB3MS_mva200	Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 200 Day MA
7042	DGS10TOTB3MS_mva050	Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 50 Day MA
7048	DGS10TODTB3_SmoothDer	Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7049	DGS10TODTB3_Log	Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
7050	DGS10TODTB3_mva200	Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3) 200 Day MA
7066	LNU03000000BYPOPTHM_SmoothDer	Derivative of Smoothed Unemployment level (NSA) / Population
7070	UNEMPLOYBYPOPTHM_YoY	Unemployment level, seasonally adjusted / Population Year over Year
7075	UNEMPLOYBYPOPTHM_SmoothDer	Derivative of Smoothed Unemployment level, seasonally adjusted / Population
7085	NPPTTLBYPOPTHM_Log	Log of ADP Private Employment / Population
7086	NPPTTLBYPOPTHM_mva200	ADP Private Employment / Population 200 Day MA
7087	NPPTTLBYPOPTHM_mva050	ADP Private Employment / Population 50 Day MA
7088	U6toU3_YoY	U6RATE minums UNRATE Year over Year
7089	U6toU3_YoY4	U6RATE minums UNRATE 4 Year over 4 Year
7091	U6toU3_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U6RATE minums UNRATE
7093	U6toU3_SmoothDer	Derivative of Smoothed U6RATE minums UNRATE
7094	U6toU3_Log	Log of U6RATE minums UNRATE
7096	U6toU3_mva050	U6RATE minums UNRATE 50 Day MA
7102	CHRISCMEHG1.by.PPIACO_SmoothDer	Derivative of Smoothed Copper, $/lb, Normalized by commodities producer price index
7111	CHRISCMEHG1.by.CPIAUCSL_SmoothDer	Derivative of Smoothed Copper, $/lb, Normalized by consumer price index
7118	DCOILBRENTEU.by.PPIACO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7120	DCOILBRENTEU.by.PPIACO_SmoothDer	Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
7122	DCOILBRENTEU.by.PPIACO_mva200	Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
7123	DCOILBRENTEU.by.PPIACO_mva050	Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 50 Day MA
7127	DCOILWTICO.by.PPIACO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7129	DCOILWTICO.by.PPIACO_SmoothDer	Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7130	DCOILWTICO.by.PPIACO_Log	Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
7131	DCOILWTICO.by.PPIACO_mva200	Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
7132	DCOILWTICO.by.PPIACO_mva050	Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 50 Day MA
7156	LBMAGOLD.USD_PM.by.GDP_SmoothDer	Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by GDP
7172	GSG.Close.by.GDPDEF_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
7174	GSG.Close.by.GDPDEF_SmoothDer	Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by GDP def
7176	GSG.Close.by.GDPDEF_mva200	GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
7177	GSG.Close.by.GDPDEF_mva050	GSCI Commodity-Indexed Trust, Normalized by GDP def 50 Day MA
7178	GSG.Close.by.GSPC.Close_YoY	GSCI Commodity-Indexed Trust, Normalized by S&P 500 Year over Year
7179	GSG.Close.by.GSPC.Close_YoY4	GSCI Commodity-Indexed Trust, Normalized by S&P 500 4 Year over 4 Year
7180	GSG.Close.by.GSPC.Close_YoY5	GSCI Commodity-Indexed Trust, Normalized by S&P 500 5 Year over 5 Year
7181	GSG.Close.by.GSPC.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
7183	GSG.Close.by.GSPC.Close_SmoothDer	Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
7184	GSG.Close.by.GSPC.Close_Log	Log of GSCI Commodity-Indexed Trust, Normalized by S&P 500
7185	GSG.Close.by.GSPC.Close_mva200	GSCI Commodity-Indexed Trust, Normalized by S&P 500 200 Day MA
7186	GSG.Close.by.GSPC.Close_mva050	GSCI Commodity-Indexed Trust, Normalized by S&P 500 50 Day MA
7194	GDPBYPOPTHM_mva200	GDP/Population 200 Day MA
7238	GSPC.DailySwing_Log	Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
7239	GSPC.DailySwing_mva200	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 200 Day MA
7262	HNFSUSNSA.minus.HSN1FNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Houses for sale - houses sold
7264	HNFSUSNSA.minus.HSN1FNSA_SmoothDer	Derivative of Smoothed Houses for sale - houses sold
7265	HNFSUSNSA.minus.HSN1FNSA_Log	Log of Houses for sale - houses sold
7266	HNFSUSNSA.minus.HSN1FNSA_mva200	Houses for sale - houses sold 200 Day MA
7267	HNFSUSNSA.minus.HSN1FNSA_mva050	Houses for sale - houses sold 50 Day MA
7280	MSPUS.times.HNFSUSNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) New privately owned 1-family units for sale times median price
7282	MSPUS.times.HNFSUSNSA_SmoothDer	Derivative of Smoothed New privately owned 1-family units for sale times median price
7283	MSPUS.times.HNFSUSNSA_Log	Log of New privately owned 1-family units for sale times median price
7284	MSPUS.times.HNFSUSNSA_mva200	New privately owned 1-family units for sale times median price 200 Day MA
7285	MSPUS.times.HNFSUSNSA_mva050	New privately owned 1-family units for sale times median price 50 Day MA
7312	MULTPLSP500PERATIOMONTH_Mean	S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

S&P 500 SMA Trends

Take a look at recent activity in the equities market. This section looks at the S&P 500 close value to the 50 day and 200 day simple moving average (SMA).

This is a longer view for the S&P 500 trend.

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-300, 300)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8
## New names:
## * `` -> ...2
## * `` -> ...5
## * `` -> ...8

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 2000)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

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S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

## Warning in max.default(structure(numeric(0), class = "Date"),
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## returning -Inf

## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

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## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrial production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

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## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 12.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 150)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 60
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 242 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 10000)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Take a look at more recent trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

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## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 35000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks. I updated this plot to include the estimated single-family home sales volume to give a sense of percentage of home sales that are cash.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).
## Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 2.5)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

# {r bond3monthlibor, echo=FALSE } # # datay <- "TB3MS" # datay_aux <- "USD1MTD156N" # ylim <- c(0, 12) # dtStart = as.Date('1985-01-01') # myPlot <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", # getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE) # myPlot <- myPlot + geom_line(data=df.data, aes_string(x="date", y=datay_aux, colour=shQuote(datay_aux)), na.rm = TRUE) # # myPlot # # Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

## geom_path: Each group consists of only one observation. Do you need to adjust
## the group aesthetic?

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(1.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

• ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.

datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 105 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 190 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 678 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065005.Q: All sectors; total mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL893065603.Q: All sectors; farm mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065603&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.